Overview

Brought to you by YData

Dataset statistics

Number of variables30
Number of observations22324
Missing cells53441
Missing cells (%)8.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 MiB
Average record size in memory240.0 B

Variable types

Categorical6
Numeric10
Text13
DateTime1

Alerts

actual_weight is highly overall correlated with horse_numberHigh correlation
finishing_position is highly overall correlated with running_position_4 and 2 other fieldsHigh correlation
horse_number is highly overall correlated with actual_weightHigh correlation
race_course is highly overall correlated with trackHigh correlation
running_position_1 is highly overall correlated with running_position_2 and 1 other fieldsHigh correlation
running_position_2 is highly overall correlated with running_position_1 and 1 other fieldsHigh correlation
running_position_3 is highly overall correlated with running_position_1 and 1 other fieldsHigh correlation
running_position_4 is highly overall correlated with finishing_positionHigh correlation
running_position_5 is highly overall correlated with finishing_positionHigh correlation
running_position_6 is highly overall correlated with finishing_positionHigh correlation
track is highly overall correlated with race_courseHigh correlation
track_condition is highly imbalanced (53.2%) Imbalance
length_behind_winner has 1898 (8.5%) missing values Missing
running_position_4 has 10057 (45.1%) missing values Missing
running_position_5 has 19521 (87.4%) missing values Missing
running_position_6 has 21900 (98.1%) missing values Missing

Reproduction

Analysis started2025-01-15 12:28:49.882839
Analysis finished2025-01-15 12:29:03.454308
Duration13.57 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

finishing_position
Categorical

High correlation 

Distinct19
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
1
1918 
4
1907 
3
1899 
2
1896 
5
1891 
Other values (14)
12813 

Length

Max length4
Median length1
Mean length1.2379502
Min length1

Characters and Unicode

Total characters27636
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row3
2nd row3
3rd row12
4th row7
5th row10

Common Values

ValueCountFrequency (%)
1 1918
8.6%
4 1907
8.5%
3 1899
8.5%
2 1896
8.5%
5 1891
8.5%
6 1890
8.5%
7 1887
8.5%
8 1877
8.4%
9 1857
8.3%
10 1822
8.2%
Other values (9) 3480
15.6%

Length

2025-01-15T17:59:03.532857image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 1918
8.6%
4 1907
8.5%
3 1899
8.5%
2 1896
8.5%
5 1891
8.5%
6 1890
8.5%
7 1887
8.5%
8 1877
8.4%
9 1857
8.3%
10 1822
8.2%
Other values (9) 3480
15.6%

Most occurring characters

ValueCountFrequency (%)
1 8961
32.4%
2 3528
 
12.8%
4 1944
 
7.0%
3 1931
 
7.0%
5 1891
 
6.8%
6 1890
 
6.8%
7 1887
 
6.8%
8 1877
 
6.8%
9 1857
 
6.7%
0 1822
 
6.6%
Other values (7) 48
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27588
99.8%
Uppercase Letter 43
 
0.2%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8961
32.5%
2 3528
 
12.8%
4 1944
 
7.0%
3 1931
 
7.0%
5 1891
 
6.9%
6 1890
 
6.9%
7 1887
 
6.8%
8 1877
 
6.8%
9 1857
 
6.7%
0 1822
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
W 18
41.9%
V 16
37.2%
A 5
 
11.6%
X 2
 
4.7%
P 1
 
2.3%
U 1
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27593
99.8%
Latin 43
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8961
32.5%
2 3528
 
12.8%
4 1944
 
7.0%
3 1931
 
7.0%
5 1891
 
6.9%
6 1890
 
6.8%
7 1887
 
6.8%
8 1877
 
6.8%
9 1857
 
6.7%
0 1822
 
6.6%
Latin
ValueCountFrequency (%)
W 18
41.9%
V 16
37.2%
A 5
 
11.6%
X 2
 
4.7%
P 1
 
2.3%
U 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27636
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8961
32.4%
2 3528
 
12.8%
4 1944
 
7.0%
3 1931
 
7.0%
5 1891
 
6.8%
6 1890
 
6.8%
7 1887
 
6.8%
8 1877
 
6.8%
9 1857
 
6.7%
0 1822
 
6.6%
Other values (7) 48
 
0.2%

horse_number
Real number (ℝ)

High correlation 

Distinct14
Distinct (%)0.1%
Missing11
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean6.8179985
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:03.645278image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile13
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.7342948
Coefficient of variation (CV)0.5477113
Kurtosis-1.1105417
Mean6.8179985
Median Absolute Deviation (MAD)3
Skewness0.099212357
Sum152130
Variance13.944958
MonotonicityNot monotonic
2025-01-15T17:59:03.751520image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 1819
 
8.1%
2 1811
 
8.1%
6 1806
 
8.1%
4 1783
 
8.0%
5 1780
 
8.0%
3 1775
 
8.0%
7 1755
 
7.9%
8 1749
 
7.8%
9 1717
 
7.7%
10 1692
 
7.6%
Other values (4) 4626
20.7%
ValueCountFrequency (%)
1 1819
8.1%
2 1811
8.1%
3 1775
8.0%
4 1783
8.0%
5 1780
8.0%
6 1806
8.1%
7 1755
7.9%
8 1749
7.8%
9 1717
7.7%
10 1692
7.6%
ValueCountFrequency (%)
14 638
 
2.9%
13 709
 
3.2%
12 1628
7.3%
11 1651
7.4%
10 1692
7.6%
9 1717
7.7%
8 1749
7.8%
7 1755
7.9%
6 1806
8.1%
5 1780
8.0%
Distinct2156
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:04.122157image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length14
Mean length12.187108
Min length3

Characters and Unicode

Total characters272065
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)0.9%

Sample

1st rowCAREFREE LET GO
2nd rowVERY RICH MAN
3rd rowFANTASTIC KAKA
4th rowVICTORY MAGIC
5th rowEXCITING DREAM
ValueCountFrequency (%)
happy 473
 
1.1%
dragon 459
 
1.0%
star 444
 
1.0%
the 428
 
1.0%
king 425
 
0.9%
lucky 418
 
0.9%
of 376
 
0.8%
super 329
 
0.7%
win 326
 
0.7%
boy 322
 
0.7%
Other values (1943) 40822
91.1%
2025-01-15T17:59:04.502870image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 26164
 
9.6%
22498
 
8.3%
A 20791
 
7.6%
R 19724
 
7.2%
I 18102
 
6.7%
N 18064
 
6.6%
O 17494
 
6.4%
T 14744
 
5.4%
L 13630
 
5.0%
S 13487
 
5.0%
Other values (19) 87367
32.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 248853
91.5%
Space Separator 22498
 
8.3%
Other Punctuation 575
 
0.2%
Dash Punctuation 139
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 26164
 
10.5%
A 20791
 
8.4%
R 19724
 
7.9%
I 18102
 
7.3%
N 18064
 
7.3%
O 17494
 
7.0%
T 14744
 
5.9%
L 13630
 
5.5%
S 13487
 
5.4%
G 9367
 
3.8%
Other values (16) 77286
31.1%
Space Separator
ValueCountFrequency (%)
22498
100.0%
Other Punctuation
ValueCountFrequency (%)
' 575
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 139
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 248853
91.5%
Common 23212
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 26164
 
10.5%
A 20791
 
8.4%
R 19724
 
7.9%
I 18102
 
7.3%
N 18064
 
7.3%
O 17494
 
7.0%
T 14744
 
5.9%
L 13630
 
5.5%
S 13487
 
5.4%
G 9367
 
3.8%
Other values (16) 77286
31.1%
Common
ValueCountFrequency (%)
22498
96.9%
' 575
 
2.5%
- 139
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 272065
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 26164
 
9.6%
22498
 
8.3%
A 20791
 
7.6%
R 19724
 
7.2%
I 18102
 
6.7%
N 18064
 
6.6%
O 17494
 
6.4%
T 14744
 
5.4%
L 13630
 
5.0%
S 13487
 
5.0%
Other values (19) 87367
32.1%
Distinct2156
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:04.797302image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters89296
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)0.9%

Sample

1st rowT059
2nd rowV286
3rd rowP363
4th rowT272
5th rowP191
ValueCountFrequency (%)
p293 39
 
0.2%
n409 39
 
0.2%
s023 39
 
0.2%
n317 38
 
0.2%
s205 38
 
0.2%
t099 37
 
0.2%
p272 37
 
0.2%
n432 35
 
0.2%
s138 35
 
0.2%
n265 34
 
0.2%
Other values (2146) 21953
98.3%
2025-01-15T17:59:05.184983image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10198
11.4%
2 9792
11.0%
3 9477
10.6%
0 9164
10.3%
4 6705
 
7.5%
S 5500
 
6.2%
T 5220
 
5.8%
8 4546
 
5.1%
5 4412
 
4.9%
9 4381
 
4.9%
Other values (11) 19901
22.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66972
75.0%
Uppercase Letter 22324
 
25.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 5500
24.6%
T 5220
23.4%
P 4160
18.6%
V 3067
13.7%
N 2215
9.9%
A 961
 
4.3%
M 797
 
3.6%
L 277
 
1.2%
K 114
 
0.5%
J 7
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 10198
15.2%
2 9792
14.6%
3 9477
14.2%
0 9164
13.7%
4 6705
10.0%
8 4546
6.8%
5 4412
6.6%
9 4381
6.5%
6 4253
6.4%
7 4044
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66972
75.0%
Latin 22324
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 5500
24.6%
T 5220
23.4%
P 4160
18.6%
V 3067
13.7%
N 2215
9.9%
A 961
 
4.3%
M 797
 
3.6%
L 277
 
1.2%
K 114
 
0.5%
J 7
 
< 0.1%
Common
ValueCountFrequency (%)
1 10198
15.2%
2 9792
14.6%
3 9477
14.2%
0 9164
13.7%
4 6705
10.0%
8 4546
6.8%
5 4412
6.6%
9 4381
6.5%
6 4253
6.4%
7 4044
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10198
11.4%
2 9792
11.0%
3 9477
10.6%
0 9164
10.3%
4 6705
 
7.5%
S 5500
 
6.2%
T 5220
 
5.8%
8 4546
 
5.1%
5 4412
 
4.9%
9 4381
 
4.9%
Other values (11) 19901
22.3%

jockey
Text

Distinct105
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:05.355878image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.2977961
Min length5

Characters and Unicode

Total characters185240
Distinct characters52
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)0.1%

Sample

1st rowM L Yeung
2nd rowU Rispoli
3rd rowB Prebble
4th rowJ Moreira
5th rowH Bowman
ValueCountFrequency (%)
k 4496
 
8.5%
c 4190
 
7.9%
n 2710
 
5.1%
h 2534
 
4.8%
m 2350
 
4.4%
y 1751
 
3.3%
j 1555
 
2.9%
t 1554
 
2.9%
moreira 1537
 
2.9%
d 1371
 
2.6%
Other values (119) 29068
54.7%
2025-01-15T17:59:05.638227image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30792
16.6%
e 15367
 
8.3%
o 10849
 
5.9%
n 9269
 
5.0%
a 9066
 
4.9%
r 7878
 
4.3%
i 7648
 
4.1%
C 7632
 
4.1%
l 7611
 
4.1%
u 5343
 
2.9%
Other values (42) 73785
39.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 101611
54.9%
Uppercase Letter 52831
28.5%
Space Separator 30792
 
16.6%
Other Punctuation 4
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 15367
15.1%
o 10849
10.7%
n 9269
9.1%
a 9066
8.9%
r 7878
7.8%
i 7648
 
7.5%
l 7611
 
7.5%
u 5343
 
5.3%
g 4826
 
4.7%
t 4416
 
4.3%
Other values (15) 19338
19.0%
Uppercase Letter
ValueCountFrequency (%)
C 7632
14.4%
M 4898
 
9.3%
K 4501
 
8.5%
H 3651
 
6.9%
L 3566
 
6.7%
N 3329
 
6.3%
T 3280
 
6.2%
W 3070
 
5.8%
Y 2769
 
5.2%
S 2718
 
5.1%
Other values (14) 13417
25.4%
Space Separator
ValueCountFrequency (%)
30792
100.0%
Other Punctuation
ValueCountFrequency (%)
' 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 154442
83.4%
Common 30798
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 15367
 
10.0%
o 10849
 
7.0%
n 9269
 
6.0%
a 9066
 
5.9%
r 7878
 
5.1%
i 7648
 
5.0%
C 7632
 
4.9%
l 7611
 
4.9%
u 5343
 
3.5%
M 4898
 
3.2%
Other values (39) 68881
44.6%
Common
ValueCountFrequency (%)
30792
> 99.9%
' 4
 
< 0.1%
- 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 185240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30792
16.6%
e 15367
 
8.3%
o 10849
 
5.9%
n 9269
 
5.0%
a 9066
 
4.9%
r 7878
 
4.3%
i 7648
 
4.1%
C 7632
 
4.1%
l 7611
 
4.1%
u 5343
 
2.9%
Other values (42) 73785
39.8%
Distinct95
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:05.774312image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length13
Mean length7.6901989
Min length4

Characters and Unicode

Total characters171676
Distinct characters49
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)0.2%

Sample

1st rowC S Shum
2nd rowT K Ng
3rd rowL Ho
4th rowJ Moore
5th rowJ Moore
ValueCountFrequency (%)
c 4424
 
7.6%
s 3989
 
6.8%
a 3555
 
6.1%
j 3188
 
5.5%
p 2826
 
4.8%
w 2708
 
4.6%
d 2504
 
4.3%
t 2452
 
4.2%
k 2351
 
4.0%
y 2297
 
3.9%
Other values (107) 28182
48.2%
2025-01-15T17:59:06.014467image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36152
21.1%
i 9165
 
5.3%
S 8519
 
5.0%
u 8386
 
4.9%
C 7309
 
4.3%
r 7189
 
4.2%
o 7117
 
4.1%
e 6383
 
3.7%
n 5752
 
3.4%
a 5573
 
3.2%
Other values (39) 70131
40.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 75266
43.8%
Uppercase Letter 59365
34.6%
Space Separator 36152
21.1%
Other Punctuation 890
 
0.5%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 9165
12.2%
u 8386
11.1%
r 7189
9.6%
o 7117
9.5%
e 6383
8.5%
n 5752
7.6%
a 5573
7.4%
l 5421
7.2%
s 4648
 
6.2%
z 3567
 
4.7%
Other values (14) 12065
16.0%
Uppercase Letter
ValueCountFrequency (%)
S 8519
14.4%
C 7309
12.3%
Y 5483
 
9.2%
T 3693
 
6.2%
A 3558
 
6.0%
L 3450
 
5.8%
F 3253
 
5.5%
M 3251
 
5.5%
J 3188
 
5.4%
W 3084
 
5.2%
Other values (12) 14577
24.6%
Space Separator
ValueCountFrequency (%)
36152
100.0%
Other Punctuation
ValueCountFrequency (%)
' 890
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 134631
78.4%
Common 37045
 
21.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 9165
 
6.8%
S 8519
 
6.3%
u 8386
 
6.2%
C 7309
 
5.4%
r 7189
 
5.3%
o 7117
 
5.3%
e 6383
 
4.7%
n 5752
 
4.3%
a 5573
 
4.1%
Y 5483
 
4.1%
Other values (36) 63755
47.4%
Common
ValueCountFrequency (%)
36152
97.6%
' 890
 
2.4%
- 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 171676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36152
21.1%
i 9165
 
5.3%
S 8519
 
5.0%
u 8386
 
4.9%
C 7309
 
4.3%
r 7189
 
4.2%
o 7117
 
4.1%
e 6383
 
3.7%
n 5752
 
3.4%
a 5573
 
3.2%
Other values (39) 70131
40.9%

actual_weight
Real number (ℝ)

High correlation 

Distinct31
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.97774
Minimum103
Maximum133
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:06.121101image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum103
5-th percentile113
Q1118
median123
Q3128
95-th percentile133
Maximum133
Range30
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.3403305
Coefficient of variation (CV)0.051556734
Kurtosis-0.67505182
Mean122.97774
Median Absolute Deviation (MAD)5
Skewness-0.26406946
Sum2745355
Variance40.199791
MonotonicityNot monotonic
2025-01-15T17:59:06.227970image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
126 1560
 
7.0%
133 1473
 
6.6%
123 1259
 
5.6%
125 1252
 
5.6%
120 1165
 
5.2%
121 1095
 
4.9%
122 1061
 
4.8%
124 1049
 
4.7%
127 1047
 
4.7%
128 995
 
4.5%
Other values (21) 10368
46.4%
ValueCountFrequency (%)
103 13
 
0.1%
104 17
 
0.1%
105 34
 
0.2%
106 31
 
0.1%
107 60
 
0.3%
108 120
0.5%
109 110
 
0.5%
110 107
 
0.5%
111 265
1.2%
112 295
1.3%
ValueCountFrequency (%)
133 1473
6.6%
132 768
3.4%
131 989
4.4%
130 915
4.1%
129 902
4.0%
128 995
4.5%
127 1047
4.7%
126 1560
7.0%
125 1252
5.6%
124 1049
4.7%
Distinct387
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:06.509413image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9673446
Min length1

Characters and Unicode

Total characters88567
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)0.1%

Sample

1st row1060
2nd row1057
3rd row1125
4th row1154
5th row1079
ValueCountFrequency (%)
1088 177
 
0.8%
1094 162
 
0.7%
1093 162
 
0.7%
1102 157
 
0.7%
1099 155
 
0.7%
1097 155
 
0.7%
1092 154
 
0.7%
1083 153
 
0.7%
1080 152
 
0.7%
1106 151
 
0.7%
Other values (377) 20746
92.9%
2025-01-15T17:59:06.906448image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 36509
41.2%
0 13769
 
15.5%
2 5929
 
6.7%
9 5262
 
5.9%
8 4713
 
5.3%
6 4607
 
5.2%
3 4461
 
5.0%
4 4461
 
5.0%
5 4437
 
5.0%
7 4417
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88565
> 99.9%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 36509
41.2%
0 13769
 
15.5%
2 5929
 
6.7%
9 5262
 
5.9%
8 4713
 
5.3%
6 4607
 
5.2%
3 4461
 
5.0%
4 4461
 
5.0%
5 4437
 
5.0%
7 4417
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88567
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 36509
41.2%
0 13769
 
15.5%
2 5929
 
6.7%
9 5262
 
5.9%
8 4713
 
5.3%
6 4607
 
5.2%
3 4461
 
5.0%
4 4461
 
5.0%
5 4437
 
5.0%
7 4417
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88567
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 36509
41.2%
0 13769
 
15.5%
2 5929
 
6.7%
9 5262
 
5.9%
8 4713
 
5.3%
6 4607
 
5.2%
3 4461
 
5.0%
4 4461
 
5.0%
5 4437
 
5.0%
7 4417
 
5.0%

draw
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2
1831 
5
1809 
7
1808 
3
1792 
6
1774 
Other values (10)
13310 

Length

Max length3
Median length1
Mean length1.2804605
Min length1

Characters and Unicode

Total characters28585
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row9
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 1831
8.2%
5 1809
 
8.1%
7 1808
 
8.1%
3 1792
 
8.0%
6 1774
 
7.9%
8 1773
 
7.9%
4 1772
 
7.9%
9 1770
 
7.9%
1 1752
 
7.8%
10 1702
 
7.6%
Other values (5) 4541
20.3%

Length

2025-01-15T17:59:07.054380image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 1831
8.2%
5 1809
 
8.1%
7 1808
 
8.1%
3 1792
 
8.0%
6 1774
 
7.9%
8 1773
 
7.9%
4 1772
 
7.9%
9 1770
 
7.9%
1 1752
 
7.8%
10 1702
 
7.6%
Other values (5) 4541
20.3%

Most occurring characters

ValueCountFrequency (%)
1 9615
33.6%
2 3395
 
11.9%
3 2478
 
8.7%
4 2407
 
8.4%
5 1809
 
6.3%
7 1808
 
6.3%
6 1774
 
6.2%
8 1773
 
6.2%
9 1770
 
6.2%
0 1702
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28531
99.8%
Dash Punctuation 54
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9615
33.7%
2 3395
 
11.9%
3 2478
 
8.7%
4 2407
 
8.4%
5 1809
 
6.3%
7 1808
 
6.3%
6 1774
 
6.2%
8 1773
 
6.2%
9 1770
 
6.2%
0 1702
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28585
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9615
33.6%
2 3395
 
11.9%
3 2478
 
8.7%
4 2407
 
8.4%
5 1809
 
6.3%
7 1808
 
6.3%
6 1774
 
6.2%
8 1773
 
6.2%
9 1770
 
6.2%
0 1702
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28585
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9615
33.6%
2 3395
 
11.9%
3 2478
 
8.7%
4 2407
 
8.4%
5 1809
 
6.3%
7 1808
 
6.3%
6 1774
 
6.2%
8 1773
 
6.2%
9 1770
 
6.2%
0 1702
 
6.0%

length_behind_winner
Text

Missing 

Distinct176
Distinct (%)0.9%
Missing1898
Missing (%)8.5%
Memory size174.5 KiB
2025-01-15T17:59:07.265952image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.9264173
Min length1

Characters and Unicode

Total characters80201
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)0.2%

Sample

1st row2
2nd row3/4
3rd row7-1/4
4th row3-1/2
5th row4-3/4
ValueCountFrequency (%)
3-1/2 713
 
3.5%
2-3/4 707
 
3.5%
4-1/4 705
 
3.5%
3 705
 
3.5%
2-1/2 702
 
3.4%
2-1/4 687
 
3.4%
2 685
 
3.4%
3-3/4 675
 
3.3%
3-1/4 672
 
3.3%
4-1/2 657
 
3.2%
Other values (163) 13518
66.2%
2025-01-15T17:59:07.611223image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 14817
18.5%
1 14005
17.5%
- 13951
17.4%
4 12525
15.6%
2 8280
10.3%
3 7976
9.9%
5 2188
 
2.7%
6 1694
 
2.1%
7 1276
 
1.6%
8 984
 
1.2%
Other values (12) 2505
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50040
62.4%
Other Punctuation 14817
 
18.5%
Dash Punctuation 13951
 
17.4%
Uppercase Letter 1391
 
1.7%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14005
28.0%
4 12525
25.0%
2 8280
16.5%
3 7976
15.9%
5 2188
 
4.4%
6 1694
 
3.4%
7 1276
 
2.5%
8 984
 
2.0%
9 676
 
1.4%
0 436
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
N 472
33.9%
H 373
26.8%
S 298
21.4%
D 130
 
9.3%
O 56
 
4.0%
E 55
 
4.0%
M 3
 
0.2%
L 3
 
0.2%
T 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/ 14817
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13951
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78810
98.3%
Latin 1391
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 14817
18.8%
1 14005
17.8%
- 13951
17.7%
4 12525
15.9%
2 8280
10.5%
3 7976
10.1%
5 2188
 
2.8%
6 1694
 
2.1%
7 1276
 
1.6%
8 984
 
1.2%
Other values (3) 1114
 
1.4%
Latin
ValueCountFrequency (%)
N 472
33.9%
H 373
26.8%
S 298
21.4%
D 130
 
9.3%
O 56
 
4.0%
E 55
 
4.0%
M 3
 
0.2%
L 3
 
0.2%
T 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80201
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 14817
18.5%
1 14005
17.5%
- 13951
17.4%
4 12525
15.6%
2 8280
10.3%
3 7976
9.9%
5 2188
 
2.7%
6 1694
 
2.1%
7 1276
 
1.6%
8 984
 
1.2%
Other values (12) 2505
 
3.1%

running_position_1
Real number (ℝ)

High correlation 

Distinct14
Distinct (%)0.1%
Missing18
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean6.7725276
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:07.720486image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile13
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.6866615
Coefficient of variation (CV)0.54435533
Kurtosis-1.0902587
Mean6.7725276
Median Absolute Deviation (MAD)3
Skewness0.10190837
Sum151068
Variance13.591473
MonotonicityNot monotonic
2025-01-15T17:59:07.822368image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
7 1822
8.2%
4 1822
8.2%
3 1808
8.1%
6 1806
8.1%
5 1802
8.1%
1 1800
8.1%
9 1779
8.0%
2 1773
7.9%
8 1762
7.9%
10 1732
 
7.8%
Other values (4) 4400
19.7%
ValueCountFrequency (%)
1 1800
8.1%
2 1773
7.9%
3 1808
8.1%
4 1822
8.2%
5 1802
8.1%
6 1806
8.1%
7 1822
8.2%
8 1762
7.9%
9 1779
8.0%
10 1732
7.8%
ValueCountFrequency (%)
14 561
 
2.5%
13 684
 
3.1%
12 1532
6.9%
11 1623
7.3%
10 1732
7.8%
9 1779
8.0%
8 1762
7.9%
7 1822
8.2%
6 1806
8.1%
5 1802
8.1%

running_position_2
Real number (ℝ)

High correlation 

Distinct14
Distinct (%)0.1%
Missing18
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean6.7458083
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:07.921275image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile13
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.6723381
Coefficient of variation (CV)0.54438816
Kurtosis-1.0929467
Mean6.7458083
Median Absolute Deviation (MAD)3
Skewness0.098190764
Sum150472
Variance13.486067
MonotonicityNot monotonic
2025-01-15T17:59:08.023688image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
6 1834
8.2%
4 1824
8.2%
1 1820
8.2%
7 1810
8.1%
2 1796
8.0%
8 1792
8.0%
3 1792
8.0%
5 1790
8.0%
9 1778
8.0%
10 1729
 
7.7%
Other values (4) 4341
19.4%
ValueCountFrequency (%)
1 1820
8.2%
2 1796
8.0%
3 1792
8.0%
4 1824
8.2%
5 1790
8.0%
6 1834
8.2%
7 1810
8.1%
8 1792
8.0%
9 1778
8.0%
10 1729
7.7%
ValueCountFrequency (%)
14 501
 
2.2%
13 677
 
3.0%
12 1528
6.8%
11 1635
7.3%
10 1729
7.7%
9 1778
8.0%
8 1792
8.0%
7 1810
8.1%
6 1834
8.2%
5 1790
8.0%

running_position_3
Real number (ℝ)

High correlation 

Distinct14
Distinct (%)0.1%
Missing18
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean6.6240025
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:08.121150image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile12
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.6021209
Coefficient of variation (CV)0.54379824
Kurtosis-1.0969334
Mean6.6240025
Median Absolute Deviation (MAD)3
Skewness0.09433434
Sum147755
Variance12.975275
MonotonicityNot monotonic
2025-01-15T17:59:08.224200image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 1878
8.4%
5 1868
8.4%
6 1846
8.3%
7 1835
8.2%
3 1833
8.2%
8 1830
8.2%
4 1830
8.2%
2 1816
8.1%
9 1774
7.9%
10 1748
7.8%
Other values (4) 4048
18.1%
ValueCountFrequency (%)
1 1878
8.4%
2 1816
8.1%
3 1833
8.2%
4 1830
8.2%
5 1868
8.4%
6 1846
8.3%
7 1835
8.2%
8 1830
8.2%
9 1774
7.9%
10 1748
7.8%
ValueCountFrequency (%)
14 347
 
1.6%
13 488
 
2.2%
12 1534
6.9%
11 1679
7.5%
10 1748
7.8%
9 1774
7.9%
8 1830
8.2%
7 1835
8.2%
6 1846
8.3%
5 1868
8.4%

running_position_4
Real number (ℝ)

High correlation  Missing 

Distinct14
Distinct (%)0.1%
Missing10057
Missing (%)45.1%
Infinite0
Infinite (%)0.0%
Mean6.492704
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:08.320532image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4908758
Coefficient of variation (CV)0.53766132
Kurtosis-1.1421259
Mean6.492704
Median Absolute Deviation (MAD)3
Skewness0.057227075
Sum79646
Variance12.186214
MonotonicityNot monotonic
2025-01-15T17:59:08.420782image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3 1041
 
4.7%
6 1037
 
4.6%
1 1036
 
4.6%
7 1032
 
4.6%
4 1028
 
4.6%
9 1028
 
4.6%
5 1027
 
4.6%
2 1019
 
4.6%
8 1007
 
4.5%
10 999
 
4.5%
Other values (4) 2013
 
9.0%
(Missing) 10057
45.1%
ValueCountFrequency (%)
1 1036
4.6%
2 1019
4.6%
3 1041
4.7%
4 1028
4.6%
5 1027
4.6%
6 1037
4.6%
7 1032
4.6%
8 1007
4.5%
9 1028
4.6%
10 999
4.5%
ValueCountFrequency (%)
14 77
 
0.3%
13 97
 
0.4%
12 890
4.0%
11 949
4.3%
10 999
4.5%
9 1028
4.6%
8 1007
4.5%
7 1032
4.6%
6 1037
4.6%
5 1027
4.6%
Distinct3728
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:08.656269image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.9965956
Min length3

Characters and Unicode

Total characters156192
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1047 ?
Unique (%)4.7%

Sample

1st row1.09.33
2nd row1.10.53
3rd row1.36.13
4th row1.11.77
5th row1.23.02
ValueCountFrequency (%)
1.10.50 48
 
0.2%
1.10.64 47
 
0.2%
1.10.72 46
 
0.2%
1.10.42 44
 
0.2%
1.10.37 44
 
0.2%
1.10.43 43
 
0.2%
1.10.45 43
 
0.2%
1.10.35 43
 
0.2%
1.10.80 43
 
0.2%
1.10.82 42
 
0.2%
Other values (3718) 21881
98.0%
2025-01-15T17:59:09.019170image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 44610
28.6%
1 33030
21.1%
0 14291
 
9.1%
2 12013
 
7.7%
4 9611
 
6.2%
3 9124
 
5.8%
5 8526
 
5.5%
9 7285
 
4.7%
8 6122
 
3.9%
7 5895
 
3.8%
Other values (2) 5685
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 111525
71.4%
Other Punctuation 44610
 
28.6%
Dash Punctuation 57
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 33030
29.6%
0 14291
12.8%
2 12013
 
10.8%
4 9611
 
8.6%
3 9124
 
8.2%
5 8526
 
7.6%
9 7285
 
6.5%
8 6122
 
5.5%
7 5895
 
5.3%
6 5628
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 44610
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 156192
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 44610
28.6%
1 33030
21.1%
0 14291
 
9.1%
2 12013
 
7.7%
4 9611
 
6.2%
3 9124
 
5.8%
5 8526
 
5.5%
9 7285
 
4.7%
8 6122
 
3.9%
7 5895
 
3.8%
Other values (2) 5685
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156192
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 44610
28.6%
1 33030
21.1%
0 14291
 
9.1%
2 12013
 
7.7%
4 9611
 
6.2%
3 9124
 
5.8%
5 8526
 
5.5%
9 7285
 
4.7%
8 6122
 
3.9%
7 5895
 
3.8%
Other values (2) 5685
 
3.6%
Distinct181
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:09.280208image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.2794302
Min length1

Characters and Unicode

Total characters50886
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9.2
2nd row19
3rd row19
4th row13
5th row14
ValueCountFrequency (%)
99 2168
 
9.7%
10 732
 
3.3%
11 680
 
3.0%
12 671
 
3.0%
13 599
 
2.7%
15 530
 
2.4%
14 514
 
2.3%
16 487
 
2.2%
17 446
 
2.0%
18 361
 
1.6%
Other values (171) 15136
67.8%
2025-01-15T17:59:09.667868image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7840
15.4%
9 7082
13.9%
. 7014
13.8%
2 5391
10.6%
3 4638
9.1%
4 3965
7.8%
5 3626
7.1%
6 3485
6.8%
7 3144
6.2%
8 3061
 
6.0%
Other values (2) 1640
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43818
86.1%
Other Punctuation 7014
 
13.8%
Dash Punctuation 54
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7840
17.9%
9 7082
16.2%
2 5391
12.3%
3 4638
10.6%
4 3965
9.0%
5 3626
8.3%
6 3485
8.0%
7 3144
7.2%
8 3061
 
7.0%
0 1586
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 7014
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50886
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7840
15.4%
9 7082
13.9%
. 7014
13.8%
2 5391
10.6%
3 4638
9.1%
4 3965
7.8%
5 3626
7.1%
6 3485
6.8%
7 3144
6.2%
8 3061
 
6.0%
Other values (2) 1640
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7840
15.4%
9 7082
13.9%
. 7014
13.8%
2 5391
10.6%
3 4638
9.1%
4 3965
7.8%
5 3626
7.1%
6 3485
6.8%
7 3144
6.2%
8 3061
 
6.0%
Other values (2) 1640
 
3.2%

running_position_5
Real number (ℝ)

High correlation  Missing 

Distinct14
Distinct (%)0.5%
Missing19521
Missing (%)87.4%
Infinite0
Infinite (%)0.0%
Mean6.3178737
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:09.777389image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4083166
Coefficient of variation (CV)0.5394721
Kurtosis-1.1630624
Mean6.3178737
Median Absolute Deviation (MAD)3
Skewness0.061489895
Sum17709
Variance11.616622
MonotonicityNot monotonic
2025-01-15T17:59:09.876243image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
4 252
 
1.1%
2 250
 
1.1%
8 248
 
1.1%
7 245
 
1.1%
1 245
 
1.1%
6 239
 
1.1%
3 235
 
1.1%
5 232
 
1.0%
9 228
 
1.0%
10 226
 
1.0%
Other values (4) 403
 
1.8%
(Missing) 19521
87.4%
ValueCountFrequency (%)
1 245
1.1%
2 250
1.1%
3 235
1.1%
4 252
1.1%
5 232
1.0%
6 239
1.1%
7 245
1.1%
8 248
1.1%
9 228
1.0%
10 226
1.0%
ValueCountFrequency (%)
14 3
 
< 0.1%
13 6
 
< 0.1%
12 192
0.9%
11 202
0.9%
10 226
1.0%
9 228
1.0%
8 248
1.1%
7 245
1.1%
6 239
1.1%
5 232
1.0%

running_position_6
Real number (ℝ)

High correlation  Missing 

Distinct12
Distinct (%)2.8%
Missing21900
Missing (%)98.1%
Infinite0
Infinite (%)0.0%
Mean6.0990566
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:09.974585image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.2875723
Coefficient of variation (CV)0.53902964
Kurtosis-1.0985686
Mean6.0990566
Median Absolute Deviation (MAD)3
Skewness0.12894774
Sum2586
Variance10.808131
MonotonicityNot monotonic
2025-01-15T17:59:10.068202image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 44
 
0.2%
4 42
 
0.2%
3 42
 
0.2%
5 39
 
0.2%
7 38
 
0.2%
1 37
 
0.2%
6 36
 
0.2%
2 35
 
0.2%
10 32
 
0.1%
9 28
 
0.1%
Other values (2) 51
 
0.2%
(Missing) 21900
98.1%
ValueCountFrequency (%)
1 37
0.2%
2 35
0.2%
3 42
0.2%
4 42
0.2%
5 39
0.2%
6 36
0.2%
7 38
0.2%
8 44
0.2%
9 28
0.1%
10 32
0.1%
ValueCountFrequency (%)
12 23
0.1%
11 28
0.1%
10 32
0.1%
9 28
0.1%
8 44
0.2%
7 38
0.2%
6 36
0.2%
5 39
0.2%
4 42
0.2%
3 42
0.2%
Distinct2367
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:10.284765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters178592
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016-070
2nd row2016-438
3rd row2015-249
4th row2014-643
5th row2015-252
ValueCountFrequency (%)
2016-769 14
 
0.1%
2015-461 14
 
0.1%
2016-468 14
 
0.1%
2015-607 14
 
0.1%
2016-805 14
 
0.1%
2014-120 13
 
0.1%
2014-423 13
 
0.1%
2014-084 13
 
0.1%
2014-379 13
 
0.1%
2014-005 13
 
0.1%
Other values (2357) 22189
99.4%
2025-01-15T17:59:10.634436image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 29692
16.6%
1 29644
16.6%
0 29640
16.6%
- 22324
12.5%
6 14865
8.3%
5 14748
8.3%
4 14647
8.2%
3 7332
 
4.1%
7 6935
 
3.9%
8 4450
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 156268
87.5%
Dash Punctuation 22324
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 29692
19.0%
1 29644
19.0%
0 29640
19.0%
6 14865
9.5%
5 14748
9.4%
4 14647
9.4%
3 7332
 
4.7%
7 6935
 
4.4%
8 4450
 
2.8%
9 4315
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 22324
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 178592
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 29692
16.6%
1 29644
16.6%
0 29640
16.6%
- 22324
12.5%
6 14865
8.3%
5 14748
8.3%
4 14647
8.2%
3 7332
 
4.1%
7 6935
 
3.9%
8 4450
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 178592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 29692
16.6%
1 29644
16.6%
0 29640
16.6%
- 22324
12.5%
6 14865
8.3%
5 14748
8.3%
4 14647
8.2%
3 7332
 
4.1%
7 6935
 
3.9%
8 4450
 
2.5%

src
Text

Distinct2367
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:10.810005image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length15
Mean length15.079242
Min length15

Characters and Unicode

Total characters336629
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20161001-6.html
2nd row20170222-3.html
3rd row20151213-6.html
4th row20150524-10.html
5th row20151213-9.html
ValueCountFrequency (%)
20170701-1.html 14
 
0.1%
20160306-9.html 14
 
0.1%
20170305-7.html 14
 
0.1%
20160501-7.html 14
 
0.1%
20170716-9.html 14
 
0.1%
20141026-10.html 13
 
0.1%
20150301-3.html 13
 
0.1%
20141012-10.html 13
 
0.1%
20150207-7.html 13
 
0.1%
20140914-5.html 13
 
0.1%
Other values (2357) 22189
99.4%
2025-01-15T17:59:11.073442image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 50884
15.1%
1 48968
14.5%
2 37504
11.1%
- 22324
6.6%
. 22324
6.6%
m 22324
6.6%
t 22324
6.6%
h 22324
6.6%
l 22324
6.6%
6 14128
 
4.2%
Other values (6) 51201
15.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 202685
60.2%
Lowercase Letter 89296
26.5%
Dash Punctuation 22324
 
6.6%
Other Punctuation 22324
 
6.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 50884
25.1%
1 48968
24.2%
2 37504
18.5%
6 14128
 
7.0%
5 14091
 
7.0%
7 10549
 
5.2%
4 9507
 
4.7%
3 7259
 
3.6%
9 5338
 
2.6%
8 4457
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
m 22324
25.0%
t 22324
25.0%
h 22324
25.0%
l 22324
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 22324
100.0%
Other Punctuation
ValueCountFrequency (%)
. 22324
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 247333
73.5%
Latin 89296
 
26.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 50884
20.6%
1 48968
19.8%
2 37504
15.2%
- 22324
9.0%
. 22324
9.0%
6 14128
 
5.7%
5 14091
 
5.7%
7 10549
 
4.3%
4 9507
 
3.8%
3 7259
 
2.9%
Other values (2) 9795
 
4.0%
Latin
ValueCountFrequency (%)
m 22324
25.0%
t 22324
25.0%
h 22324
25.0%
l 22324
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 336629
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 50884
15.1%
1 48968
14.5%
2 37504
11.1%
- 22324
6.6%
. 22324
6.6%
m 22324
6.6%
t 22324
6.6%
h 22324
6.6%
l 22324
6.6%
6 14128
 
4.2%
Other values (6) 51201
15.2%
Distinct254
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
Minimum2014-09-14 00:00:00
Maximum2017-07-16 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-01-15T17:59:11.205091image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:59:11.331886image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

race_course
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
Sha Tin
14337 
Happy Valley
7987 

Length

Max length12
Median length7
Mean length8.7888819
Min length7

Characters and Unicode

Total characters196203
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSha Tin
2nd rowHappy Valley
3rd rowSha Tin
4th rowSha Tin
5th rowSha Tin

Common Values

ValueCountFrequency (%)
Sha Tin 14337
64.2%
Happy Valley 7987
35.8%

Length

2025-01-15T17:59:11.448311image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-15T17:59:11.549141image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
sha 14337
32.1%
tin 14337
32.1%
happy 7987
17.9%
valley 7987
17.9%

Most occurring characters

ValueCountFrequency (%)
a 30311
15.4%
22324
11.4%
l 15974
8.1%
y 15974
8.1%
p 15974
8.1%
T 14337
7.3%
h 14337
7.3%
S 14337
7.3%
i 14337
7.3%
n 14337
7.3%
Other values (3) 23961
12.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 129231
65.9%
Uppercase Letter 44648
 
22.8%
Space Separator 22324
 
11.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 30311
23.5%
l 15974
12.4%
y 15974
12.4%
p 15974
12.4%
h 14337
11.1%
i 14337
11.1%
n 14337
11.1%
e 7987
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
T 14337
32.1%
S 14337
32.1%
H 7987
17.9%
V 7987
17.9%
Space Separator
ValueCountFrequency (%)
22324
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 173879
88.6%
Common 22324
 
11.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 30311
17.4%
l 15974
9.2%
y 15974
9.2%
p 15974
9.2%
T 14337
8.2%
h 14337
8.2%
S 14337
8.2%
i 14337
8.2%
n 14337
8.2%
H 7987
 
4.6%
Other values (2) 15974
9.2%
Common
ValueCountFrequency (%)
22324
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 196203
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 30311
15.4%
22324
11.4%
l 15974
8.1%
y 15974
8.1%
p 15974
8.1%
T 14337
7.3%
h 14337
7.3%
S 14337
7.3%
i 14337
7.3%
n 14337
7.3%
Other values (3) 23961
12.2%

race_number
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2542555
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:11.647617image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q38
95-th percentile10
Maximum11
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.7969628
Coefficient of variation (CV)0.53232333
Kurtosis-1.0479961
Mean5.2542555
Median Absolute Deviation (MAD)2
Skewness0.13401981
Sum117296
Variance7.8230007
MonotonicityNot monotonic
2025-01-15T17:59:11.749552image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
4 2431
10.9%
5 2411
10.8%
6 2400
10.8%
2 2392
10.7%
7 2376
10.6%
8 2366
10.6%
3 2357
10.6%
1 2345
10.5%
9 1477
6.6%
10 1395
6.2%
ValueCountFrequency (%)
1 2345
10.5%
2 2392
10.7%
3 2357
10.6%
4 2431
10.9%
5 2411
10.8%
6 2400
10.8%
7 2376
10.6%
8 2366
10.6%
9 1477
6.6%
10 1395
6.2%
ValueCountFrequency (%)
11 374
 
1.7%
10 1395
6.2%
9 1477
6.6%
8 2366
10.6%
7 2376
10.6%
6 2400
10.8%
5 2411
10.8%
4 2431
10.9%
3 2357
10.6%
2 2392
10.7%

race_class
Categorical

Distinct16
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
Class 4
8224 
Class 3
7190 
Class 5
3209 
Class 2
2108 
Class 1
 
406
Other values (11)
1187 

Length

Max length27
Median length7
Mean length7.431867
Min length7

Characters and Unicode

Total characters165909
Distinct characters33
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowClass 3
2nd rowClass 4
3rd rowClass 2
4th rowClass 2
5th rowClass 1

Common Values

ValueCountFrequency (%)
Class 4 8224
36.8%
Class 3 7190
32.2%
Class 5 3209
 
14.4%
Class 2 2108
 
9.4%
Class 1 406
 
1.8%
Group One 286
 
1.3%
Hong Kong Group Three 217
 
1.0%
Griffin Race 119
 
0.5%
Group Two 119
 
0.5%
Group Three 84
 
0.4%
Other values (6) 362
 
1.6%

Length

2025-01-15T17:59:11.877571image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
class 21297
46.7%
4 8362
 
18.3%
3 7212
 
15.8%
5 3209
 
7.0%
2 2108
 
4.6%
group 861
 
1.9%
1 406
 
0.9%
hong 372
 
0.8%
kong 372
 
0.8%
one 367
 
0.8%
Other values (7) 1064
 
2.3%

Most occurring characters

ValueCountFrequency (%)
s 42723
25.8%
23306
14.0%
a 21541
13.0%
C 21375
12.9%
l 21375
12.9%
4 8362
 
5.0%
3 7212
 
4.3%
5 3209
 
1.9%
2 2108
 
1.3%
o 1954
 
1.2%
Other values (23) 12744
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 96653
58.3%
Uppercase Letter 24333
 
14.7%
Space Separator 23306
 
14.0%
Decimal Number 21297
 
12.8%
Open Punctuation 160
 
0.1%
Close Punctuation 160
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 42723
44.2%
a 21541
22.3%
l 21375
22.1%
o 1954
 
2.0%
e 1471
 
1.5%
r 1410
 
1.5%
n 1386
 
1.4%
p 939
 
1.0%
u 861
 
0.9%
g 744
 
0.8%
Other values (7) 2249
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
C 21375
87.8%
G 980
 
4.0%
T 494
 
2.0%
H 372
 
1.5%
K 372
 
1.5%
O 367
 
1.5%
R 295
 
1.2%
S 78
 
0.3%
Decimal Number
ValueCountFrequency (%)
4 8362
39.3%
3 7212
33.9%
5 3209
 
15.1%
2 2108
 
9.9%
1 406
 
1.9%
Space Separator
ValueCountFrequency (%)
23306
100.0%
Open Punctuation
ValueCountFrequency (%)
( 160
100.0%
Close Punctuation
ValueCountFrequency (%)
) 160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 120986
72.9%
Common 44923
 
27.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 42723
35.3%
a 21541
17.8%
C 21375
17.7%
l 21375
17.7%
o 1954
 
1.6%
e 1471
 
1.2%
r 1410
 
1.2%
n 1386
 
1.1%
G 980
 
0.8%
p 939
 
0.8%
Other values (15) 5832
 
4.8%
Common
ValueCountFrequency (%)
23306
51.9%
4 8362
 
18.6%
3 7212
 
16.1%
5 3209
 
7.1%
2 2108
 
4.7%
1 406
 
0.9%
( 160
 
0.4%
) 160
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 165909
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 42723
25.8%
23306
14.0%
a 21541
13.0%
C 21375
12.9%
l 21375
12.9%
4 8362
 
5.0%
3 7212
 
4.3%
5 3209
 
1.9%
2 2108
 
1.3%
o 1954
 
1.2%
Other values (23) 12744
 
7.7%

race_distance
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1411.7273
Minimum1000
Maximum2400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:11.985300image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1000
Q11200
median1400
Q31650
95-th percentile1800
Maximum2400
Range1400
Interquartile range (IQR)450

Descriptive statistics

Standard deviation281.05686
Coefficient of variation (CV)0.19908722
Kurtosis-0.073657937
Mean1411.7273
Median Absolute Deviation (MAD)200
Skewness0.58802411
Sum31515400
Variance78992.958
MonotonicityNot monotonic
2025-01-15T17:59:12.079254image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1200 7795
34.9%
1400 3826
17.1%
1650 3660
16.4%
1000 2257
 
10.1%
1600 1982
 
8.9%
1800 1852
 
8.3%
2000 528
 
2.4%
2200 347
 
1.6%
2400 77
 
0.3%
ValueCountFrequency (%)
1000 2257
 
10.1%
1200 7795
34.9%
1400 3826
17.1%
1600 1982
 
8.9%
1650 3660
16.4%
1800 1852
 
8.3%
2000 528
 
2.4%
2200 347
 
1.6%
2400 77
 
0.3%
ValueCountFrequency (%)
2400 77
 
0.3%
2200 347
 
1.6%
2000 528
 
2.4%
1800 1852
 
8.3%
1650 3660
16.4%
1600 1982
 
8.9%
1400 3826
17.1%
1200 7795
34.9%
1000 2257
 
10.1%

track_condition
Categorical

Imbalance 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
GOOD
12204 
GOOD TO FIRM
8120 
GOOD TO YIELDING
 
1187
YIELDING
 
251
WET SLOW
 
222
Other values (4)
 
340

Length

Max length16
Median length4
Mean length7.6600968
Min length4

Characters and Unicode

Total characters171004
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGOOD
2nd rowGOOD TO FIRM
3rd rowGOOD
4th rowYIELDING
5th rowGOOD

Common Values

ValueCountFrequency (%)
GOOD 12204
54.7%
GOOD TO FIRM 8120
36.4%
GOOD TO YIELDING 1187
 
5.3%
YIELDING 251
 
1.1%
WET SLOW 222
 
1.0%
FAST 191
 
0.9%
WET FAST 132
 
0.6%
SOFT 10
 
< 0.1%
YIELDING TO SOFT 7
 
< 0.1%

Length

2025-01-15T17:59:12.194852image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-15T17:59:12.308957image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
good 21511
52.1%
to 9314
22.5%
firm 8120
 
19.7%
yielding 1445
 
3.5%
wet 354
 
0.9%
fast 323
 
0.8%
slow 222
 
0.5%
soft 17
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
O 52575
30.7%
G 22956
13.4%
D 22956
13.4%
18982
 
11.1%
I 11010
 
6.4%
T 10008
 
5.9%
F 8460
 
4.9%
R 8120
 
4.7%
M 8120
 
4.7%
E 1799
 
1.1%
Other values (6) 6018
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 152022
88.9%
Space Separator 18982
 
11.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 52575
34.6%
G 22956
15.1%
D 22956
15.1%
I 11010
 
7.2%
T 10008
 
6.6%
F 8460
 
5.6%
R 8120
 
5.3%
M 8120
 
5.3%
E 1799
 
1.2%
L 1667
 
1.1%
Other values (5) 4351
 
2.9%
Space Separator
ValueCountFrequency (%)
18982
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 152022
88.9%
Common 18982
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 52575
34.6%
G 22956
15.1%
D 22956
15.1%
I 11010
 
7.2%
T 10008
 
6.6%
F 8460
 
5.6%
R 8120
 
5.3%
M 8120
 
5.3%
E 1799
 
1.2%
L 1667
 
1.1%
Other values (5) 4351
 
2.9%
Common
ValueCountFrequency (%)
18982
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 171004
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 52575
30.7%
G 22956
13.4%
D 22956
13.4%
18982
 
11.1%
I 11010
 
6.4%
T 10008
 
5.9%
F 8460
 
4.9%
R 8120
 
4.7%
M 8120
 
4.7%
E 1799
 
1.1%
Other values (6) 6018
 
3.5%
Distinct1084
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:12.605020image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length85
Median length68
Mean length23.286508
Min length12

Characters and Unicode

Total characters519848
Distinct characters51
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSHANGHAI HANDICAP
2nd rowKWAI CHUNG HANDICAP
3rd rowEISHIN PRESTON HANDICAP
4th rowSTAUNTON HANDICAP
5th rowFLYING DANCER HANDICAP
ValueCountFrequency (%)
handicap 21681
28.1%
the 3556
 
4.6%
cup 2003
 
2.6%
kong 910
 
1.2%
hong 795
 
1.0%
club 716
 
0.9%
challenge 649
 
0.8%
trophy 573
 
0.7%
shan 503
 
0.7%
tai 495
 
0.6%
Other values (1186) 45203
58.6%
2025-01-15T17:59:13.045233image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 68090
13.1%
54760
10.5%
N 46477
 
8.9%
I 41549
 
8.0%
H 37346
 
7.2%
C 36292
 
7.0%
P 30356
 
5.8%
E 28104
 
5.4%
D 27068
 
5.2%
O 19244
 
3.7%
Other values (41) 130562
25.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 457726
88.0%
Space Separator 54760
 
10.5%
Close Punctuation 2699
 
0.5%
Open Punctuation 2699
 
0.5%
Other Punctuation 1094
 
0.2%
Decimal Number 525
 
0.1%
Dash Punctuation 281
 
0.1%
Lowercase Letter 64
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 68090
14.9%
N 46477
10.2%
I 41549
 
9.1%
H 37346
 
8.2%
C 36292
 
7.9%
P 30356
 
6.6%
E 28104
 
6.1%
D 27068
 
5.9%
O 19244
 
4.2%
T 17622
 
3.8%
Other values (16) 105578
23.1%
Decimal Number
ValueCountFrequency (%)
1 135
25.7%
4 78
14.9%
0 75
14.3%
3 58
11.0%
2 57
10.9%
5 47
 
9.0%
8 27
 
5.1%
9 21
 
4.0%
7 19
 
3.6%
6 8
 
1.5%
Other Punctuation
ValueCountFrequency (%)
' 646
59.0%
& 227
 
20.7%
. 194
 
17.7%
: 10
 
0.9%
, 9
 
0.8%
@ 8
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
i 29
45.3%
n 14
21.9%
a 7
 
10.9%
o 7
 
10.9%
e 7
 
10.9%
Space Separator
ValueCountFrequency (%)
54760
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2699
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2699
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 281
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 457790
88.1%
Common 62058
 
11.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 68090
14.9%
N 46477
10.2%
I 41549
 
9.1%
H 37346
 
8.2%
C 36292
 
7.9%
P 30356
 
6.6%
E 28104
 
6.1%
D 27068
 
5.9%
O 19244
 
4.2%
T 17622
 
3.8%
Other values (21) 105642
23.1%
Common
ValueCountFrequency (%)
54760
88.2%
) 2699
 
4.3%
( 2699
 
4.3%
' 646
 
1.0%
- 281
 
0.5%
& 227
 
0.4%
. 194
 
0.3%
1 135
 
0.2%
4 78
 
0.1%
0 75
 
0.1%
Other values (10) 264
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 519848
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 68090
13.1%
54760
10.5%
N 46477
 
8.9%
I 41549
 
8.0%
H 37346
 
7.2%
C 36292
 
7.0%
P 30356
 
5.8%
E 28104
 
5.4%
D 27068
 
5.2%
O 19244
 
3.7%
Other values (41) 130562
25.1%

track
Categorical

High correlation 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
TURF - "A" COURSE
4928 
TURF - "C" COURSE
4186 
TURF - "C+3" COURSE
3795 
TURF - "B" COURSE
2831 
ALL WEATHER TRACK
2726 
Other values (2)
3858 

Length

Max length19
Median length17
Mean length17.68563
Min length17

Characters and Unicode

Total characters394814
Distinct characters20
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTURF - "A+3" COURSE
2nd rowTURF - "C+3" COURSE
3rd rowTURF - "A" COURSE
4th rowTURF - "C+3" COURSE
5th rowTURF - "A" COURSE

Common Values

ValueCountFrequency (%)
TURF - "A" COURSE 4928
22.1%
TURF - "C" COURSE 4186
18.8%
TURF - "C+3" COURSE 3795
17.0%
TURF - "B" COURSE 2831
12.7%
ALL WEATHER TRACK 2726
12.2%
TURF - "B+2" COURSE 1984
8.9%
TURF - "A+3" COURSE 1874
 
8.4%

Length

2025-01-15T17:59:13.355536image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-15T17:59:13.476971image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
turf 19598
22.6%
19598
22.6%
course 19598
22.6%
a 4928
 
5.7%
c 4186
 
4.8%
c+3 3795
 
4.4%
b 2831
 
3.3%
all 2726
 
3.1%
weather 2726
 
3.1%
track 2726
 
3.1%
Other values (2) 3858
 
4.5%

Most occurring characters

ValueCountFrequency (%)
64246
16.3%
R 44648
11.3%
" 39196
9.9%
U 39196
9.9%
C 30305
7.7%
T 25050
 
6.3%
E 25050
 
6.3%
F 19598
 
5.0%
O 19598
 
5.0%
- 19598
 
5.0%
Other values (10) 68329
17.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 256468
65.0%
Space Separator 64246
 
16.3%
Other Punctuation 39196
 
9.9%
Dash Punctuation 19598
 
5.0%
Math Symbol 7653
 
1.9%
Decimal Number 7653
 
1.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 44648
17.4%
U 39196
15.3%
C 30305
11.8%
T 25050
9.8%
E 25050
9.8%
F 19598
7.6%
O 19598
7.6%
S 19598
7.6%
A 14980
 
5.8%
L 5452
 
2.1%
Other values (4) 12993
 
5.1%
Decimal Number
ValueCountFrequency (%)
3 5669
74.1%
2 1984
 
25.9%
Space Separator
ValueCountFrequency (%)
64246
100.0%
Other Punctuation
ValueCountFrequency (%)
" 39196
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19598
100.0%
Math Symbol
ValueCountFrequency (%)
+ 7653
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 256468
65.0%
Common 138346
35.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 44648
17.4%
U 39196
15.3%
C 30305
11.8%
T 25050
9.8%
E 25050
9.8%
F 19598
7.6%
O 19598
7.6%
S 19598
7.6%
A 14980
 
5.8%
L 5452
 
2.1%
Other values (4) 12993
 
5.1%
Common
ValueCountFrequency (%)
64246
46.4%
" 39196
28.3%
- 19598
 
14.2%
+ 7653
 
5.5%
3 5669
 
4.1%
2 1984
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 394814
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64246
16.3%
R 44648
11.3%
" 39196
9.9%
U 39196
9.9%
C 30305
7.7%
T 25050
 
6.3%
E 25050
 
6.3%
F 19598
 
5.0%
O 19598
 
5.0%
- 19598
 
5.0%
Other values (10) 68329
17.3%
Distinct2367
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:13.759818image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length35
Median length29
Mean length21.16592
Min length17

Characters and Unicode

Total characters472508
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row23.70 22.34 22.98
2nd row24.12 23.20 23.05
3rd row24.55 23.86 24.20 22.35
4th row23.84 23.09 24.27
5th row13.56 22.61 24.02 22.06
ValueCountFrequency (%)
23.53 608
 
0.7%
23.70 517
 
0.6%
23.20 487
 
0.6%
23.88 467
 
0.6%
23.92 454
 
0.6%
23.45 449
 
0.5%
23.81 448
 
0.5%
23.62 445
 
0.5%
23.40 443
 
0.5%
23.32 439
 
0.5%
Other values (878) 77715
94.2%
2025-01-15T17:59:14.150757image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 107346
22.7%
. 82472
17.5%
60148
12.7%
3 52275
11.1%
4 32976
 
7.0%
1 28005
 
5.9%
5 21606
 
4.6%
7 19197
 
4.1%
8 18407
 
3.9%
6 17108
 
3.6%
Other values (2) 32968
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 329888
69.8%
Other Punctuation 82472
 
17.5%
Space Separator 60148
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 107346
32.5%
3 52275
15.8%
4 32976
 
10.0%
1 28005
 
8.5%
5 21606
 
6.5%
7 19197
 
5.8%
8 18407
 
5.6%
6 17108
 
5.2%
0 16636
 
5.0%
9 16332
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 82472
100.0%
Space Separator
ValueCountFrequency (%)
60148
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 472508
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 107346
22.7%
. 82472
17.5%
60148
12.7%
3 52275
11.1%
4 32976
 
7.0%
1 28005
 
5.9%
5 21606
 
4.6%
7 19197
 
4.1%
8 18407
 
3.9%
6 17108
 
3.6%
Other values (2) 32968
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 472508
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 107346
22.7%
. 82472
17.5%
60148
12.7%
3 52275
11.1%
4 32976
 
7.0%
1 28005
 
5.9%
5 21606
 
4.6%
7 19197
 
4.1%
8 18407
 
3.9%
6 17108
 
3.6%
Other values (2) 32968
 
7.0%
Distinct2367
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size174.5 KiB
2025-01-15T17:59:15.260643image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8275
Median length2939
Mean length2425.5384
Min length92

Characters and Unicode

Total characters54147719
Distinct characters95
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row After beginning awkwardly and making contact with LUCKY GUY, ENDEARING then shifted in, resulting in CAPE THE FAITH which began awkwardly being further hampered. CALL ME AWESOME began awkwardly, shifted out and bumped the hindquarters of CAREFREE LET GO. On the first turn at the 850 Metres, CALL ME AWESOME (K C Leung) shifted out, resulting in ORIONIDS being hampered and taken wider. K C Leung advised that CALL ME AWESOME then hung out throughout the middle stages and he was unable to get the horse to relax whilst racing in the lead. He said as a consequence CALL ME AWESOME was beaten soon after straightening and then weakened in the Straight. A veterinary inspection of CALL ME AWESOME immediately following the race did not show any significant findings. Passing the 500 Metres, LAUGH OUT LOUD was steadied when momentarily tightened for room between LOVELY DELOVELY and GORGEOUS KING which shifted out slightly. CAREFREE LET GO was held up for a short distance in the early part of the Straight. Also in the early part of the Straight, LAUGH OUT LOUD was awkwardly placed outside the heels of GORGEOUS KING. When placed under pressure in the Straight, ORIONIDS raced greenly and was inclined to hang out. When questioned regarding his riding of ROUNDABOUT in the Home Straight, particularly in the early part of the Straight, D Whyte stated that after discussions with connections prior to its last start win, it was felt that ROUNDABOUT gives its best when able to be brought to the outside as the horse is reluctant to improve between runners. He said it was decided to ride ROUNDABOUT in exactly the same manner as its last start by going back from its outside barrier and bringing the horse to the extreme outside on straightening. He said on straightening he brought ROUNDABOUT to the outside and rode the horse in a hands and heels fashion in the early part of the Straight and similar to last start, the horse let down well and commenced to close off strongly. He said that he continued to ride ROUNDABOUT hands and heels before pulling the whip near the 150 Metres as ROUNDABOUT continued to close off well. D Whyte was advised that his explanation would be reported, however, he must ensure that he does not give his mounts too much to do. IRON BOY and LUCKY GUY were sent for sampling.
2nd row KWAICHUNG BROTHERS was slow to begin. GOLDEN ACHIEVER shifted in at the start and bumped AH BO. ROCKET LET WIN began only fairly and then shortly after the start was steadied when crowded for room inside VERY RICH MAN which shifted in. G-ONE LOVER shifted in at the start and bumped GAME OF FUN. From the outside barrier, BRIGHT STAR got its head up when being steadied to be shifted across behind runners in the early stages. CONTRIBUTION lost its right hind plate after the 900 Metres. Approaching and passing the 500 Metres, AH BO got its head on the side and lay out. For the majority of the race, ROCKET LET WIN travelled wide and without cover. The Stewards deferred the declaration of weighed-in as they were of the prima facie view that an incident had occurred approaching the 200 Metres which cast sufficient doubt on whether DR RACE (B Prebble) should be declared the 5th placegetter. When N Callan, the rider of the 6th placegetter, GOLDEN ACHIEVER, did not enter a formal protest/objection on behalf of the connections of GOLDEN ACHIEVER, the Stewards believed that it was appropriate for the matter to proceed to a formal/objection hearing. Whilst these placings did not affect betting, it was relevant that there was the issue of prizemoney in respect of the 5th placegetter. After taking evidence from B Prebble, Mr S K Sit, assistant trainer allocated to Mr D E Ferraris, the trainer of DR RACE, and N Callan, it was found that approaching the 200 Metres DR RACE was shifted to the outside of GAME OF FUN to obtain clear running which resulted in GOLDEN ACHIEVER being checked and losing its rightful running when crowded for room inside CONTRIBUTION. Having regard to the neck margin between both horses at the end of the race and the manner in which they were finishing off the race, the Stewards were satisfied that had the interference not occurred GOLDEN ACHIEVER would have finished in front of DR RACE. Accordingly, the protest/objection was sustained and the placings amended to read No. 3, GAME OF FUN, 1st; No. 11, CONTRIBUTION, 2nd; No. 1, VERY RICH MAN, 3rd; No. 9, G-ONE LOVER, 4th; No. 2, GOLDEN ACHIEVER, 5th; and No. 4, DR RACE, 6th. N Callan was advised that in similar circumstances he must be aware of the placings of horses and to ensure that he has the interests of connections in mind. At a subsequent inquiry, B Prebble pleaded guilty to a charge of careless riding [Rule 100(1)] and was suspended from riding in races for a period to commence on Wednesday, 8 March 2017 and to expire on Monday, 13 March 2017 on which day he may resume race riding (2 Hong Kong racedays). In assessing penalty, the Stewards took into account Jockey Prebble’s good race riding record. G-ONE LOVER, GAME OF FUN and CONTRIBUTION were sent for sampling.
3rd row PHOTON WILLIE was crowded for room on jumping between TRAVEL FIRST and PIKACHU which got its head on the side and shifted in despite the efforts of its rider. APOLLO'S CHOICE, which began awkwardly, and WAH MAY FRIEND bumped at the start. As the start was effected, REGENCY KING lifted its front feet off the ground and then from a wide barrier was shifted across behind runners in the early stages. Also from the outside barrier, WINNING LEADER was taken across behind runners in the early stages. For some distance after the 700 Metres, APOLLO'S CHOICE was awkwardly placed close to the heels of FANTASTIC KAKA. Passing the 350 Metres, WAH MAY FRIEND was awkwardly placed close to the heels of BRILLIANT SHINE after being initially disappointed for running outside that horse. PHOTON WILLIE, which was following, was shifted in away from the heels of WAH MAY FRIEND in consequence. Approaching the 300 Metres, SICHUAN DAR and REGENCY KING made contact as SICHUAN DAR improved into tight running outside WINNING LEADER. Then passing the 300 Metres, SICHUAN DAR was awkwardly placed outside the heels of WINNING LEADER when that horse was taken out by VICTORY MAGIC which was taken wider by ISHVARA. Passing the 300 Metres, PIKACHU was shifted in away from the heels of FANTASTIC KAKA which was giving ground in order to obtain clear running. Throughout the race, BRILLIANT SHINE travelled wide and without cover. The Stewards interviewed M Demuro regarding his riding out of WAH MAY FRIEND over the concluding stages. M Demuro was advised that as the Stewards could not be satisfied to the requisite degree that WAH MAY FRIEND would have finished in front of TRAVEL FIRST, having in mind that he stopped riding his horse over about the final two strides and also having regard to the neck margin between the horses at the end of the race, nonetheless he was severely reprimanded and advised to ensure that he rides his mounts out all the way to the end of the race where circumstances permit. After the race, B Prebble (FANTASTIC KAKA) reported that the horse did not feel comfortable in its action over the latter stages of the race. A veterinary inspection of FANTASTIC KAKA immediately following the race did not show any significant findings. Before being allowed to race again, FANTASTIC KAKA will be subjected to an official veterinary examination. A veterinary inspection of PHOTON WILLIE and BRILLIANT DREAM immediately following the race did not show any significant findings. VICTORY MAGIC, WERTHER and APOLLO'S CHOICE were sent for sampling.
4th row DEEP THINKER was checked when crowded for room on jumping between IMPERIAL CHAMPION and OUR FOLKS which shifted out. CLEVER BEAVER shifted out abruptly at the start, resulting in IMPERIAL ROME being crowded for room out onto DILLY which became unbalanced after being bumped by IMPERIAL ROME. MR GENUINE began awkwardly, shifted out and bumped the hindquarters of GOLDEN DEER, causing both horses to become unbalanced. After this, MR GENUINE and GOLDEN DEER were shifted across behind runners. Near the 1150 Metres, DINING WORLD was hampered and lost ground when crowded for room inside OUR FOLKS (Apprentice H N Wong) which shifted in. Apprentice Wong was severely reprimanded and advised that in similar circumstances he would be expected to make every endeavour to prevent his mounts from shifting ground. Near the 600 Metres, MR GENUINE was steadied away from the heels of OUR FOLKS. Rounding the Home Turn, MR GENUINE raced in restricted room between OUR FOLKS and DEEP THINKER which shifted out. At the entrance to the Straight, DEEP THINKER was shifted to the inside of VICTORY MAGIC to obtain clear running. Passing the 350 Metres, MR GENUINE was steadied and shifted to the outside of VICTORY MAGIC. Passing the 200 Metres, VICTORY MAGIC was shifted out away from the heels of DEEP THINKER which shifted to the outside of ALL GREAT FRIENDS. Near the 150 Metres, J Moreira (VICTORY MAGIC) momentarily lost the use of his whip. After the race, D Whyte stated that DINING WORLD did not stretch out on today’s track at any stage of the race and never travelled comfortably. A veterinary inspection of DINING WORLD immediately following the race did not show any significant findings. A veterinary inspection of DILLY immediately following the race did not show any significant findings. DEEP THINKER and STRATHMORE were sent for sampling.
5th row DIVINE CALLING was withdrawn on 12.12.15 by order of the Stewards acting on veterinary advice (inappetence) and was replaced by Standby Declared Starter KABAYAN (U Rispoli). Before being allowed to race again, DIVINE CALLING will be subjected to an official veterinary examination. KABAYAN was slow to begin. LUCKY BUBBLES began awkwardly. PACKING LLAREGYB began only fairly. SUN JEWELLERY and SUPER LIFELINE bumped at the start. From a wide barrier, I'M IN CHARGE got its head up on a number of occasions when being steadied to be taken across behind runners in the early stages. Making the turn after the 900 Metres, KABAYAN commenced to travel keenly and shifted out away from the heels of I'M IN CHARGE which was awkwardly placed close to the heels of GURUS DREAM. After this, KABAYAN travelled wide and without cover. When questioned regarding his riding of PACKING LLAREGYB in the early part of the Straight, M Demuro stated that his mount was unbalanced after making the Home Turn and was inclined to get its head on the side and lay in. He said he took some time to balance the horse before being able to place it under pressure prior to the 300 Metres. He said after this PACKING LLAREGYB finished off the race fairly. A veterinary inspection of I'M IN CHARGE and EXCITING DREAM immediately following the race did not show any significant findings. SUN JEWELLERY and MULTIVICTORY were sent for sampling.
ValueCountFrequency (%)
the 621770
 
6.9%
to 314062
 
3.5%
and 263309
 
2.9%
was 241895
 
2.7%
of 216435
 
2.4%
in 207619
 
2.3%
metres 122349
 
1.4%
race 112081
 
1.2%
he 107275
 
1.2%
a 106710
 
1.2%
Other values (5699) 6684506
74.3%
2025-01-15T17:59:16.573820image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9247406
17.1%
e 4528203
 
8.4%
t 3303096
 
6.1%
a 2847244
 
5.3%
i 2734409
 
5.0%
n 2612038
 
4.8%
r 2324317
 
4.3%
o 2270641
 
4.2%
s 2082270
 
3.8%
h 1882573
 
3.5%
Other values (85) 20315522
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34672182
64.0%
Space Separator 9247819
 
17.1%
Uppercase Letter 8488498
 
15.7%
Other Punctuation 835014
 
1.5%
Decimal Number 493298
 
0.9%
Control 328082
 
0.6%
Open Punctuation 32274
 
0.1%
Close Punctuation 32274
 
0.1%
Dash Punctuation 9091
 
< 0.1%
Math Symbol 5903
 
< 0.1%
Other values (3) 3284
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4528203
13.1%
t 3303096
 
9.5%
a 2847244
 
8.2%
i 2734409
 
7.9%
n 2612038
 
7.5%
r 2324317
 
6.7%
o 2270641
 
6.5%
s 2082270
 
6.0%
h 1882573
 
5.4%
d 1813566
 
5.2%
Other values (18) 8273825
23.9%
Uppercase Letter
ValueCountFrequency (%)
E 806912
 
9.5%
A 755200
 
8.9%
R 630608
 
7.4%
N 589692
 
6.9%
I 578183
 
6.8%
O 568308
 
6.7%
T 503518
 
5.9%
S 486266
 
5.7%
L 431627
 
5.1%
M 389346
 
4.6%
Other values (17) 2748838
32.4%
Decimal Number
ValueCountFrequency (%)
0 252901
51.3%
1 77156
 
15.6%
2 39132
 
7.9%
5 38077
 
7.7%
3 18585
 
3.8%
6 16661
 
3.4%
7 13657
 
2.8%
4 13519
 
2.7%
9 12991
 
2.6%
8 10619
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 427105
51.1%
, 385357
46.1%
' 13486
 
1.6%
/ 6677
 
0.8%
" 972
 
0.1%
¿ 972
 
0.1%
; 212
 
< 0.1%
? 192
 
< 0.1%
: 41
 
< 0.1%
Control
ValueCountFrequency (%)
288468
87.9%
€ 19724
 
6.0%
™ 17883
 
5.5%
 863
 
0.3%
œ 695
 
0.2%
˜ 205
 
0.1%
166
 
0.1%
“ 78
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
> 2932
49.7%
< 2932
49.7%
+ 39
 
0.7%
Space Separator
ValueCountFrequency (%)
9247406
> 99.9%
  413
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 30080
93.2%
[ 2194
 
6.8%
Close Punctuation
ValueCountFrequency (%)
) 30080
93.2%
] 2194
 
6.8%
Dash Punctuation
ValueCountFrequency (%)
- 9091
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 2271
100.0%
Other Number
ValueCountFrequency (%)
½ 993
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 43160680
79.7%
Common 10987039
 
20.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4528203
 
10.5%
t 3303096
 
7.7%
a 2847244
 
6.6%
i 2734409
 
6.3%
n 2612038
 
6.1%
r 2324317
 
5.4%
o 2270641
 
5.3%
s 2082270
 
4.8%
h 1882573
 
4.4%
d 1813566
 
4.2%
Other values (45) 16762323
38.8%
Common
ValueCountFrequency (%)
9247406
84.2%
. 427105
 
3.9%
, 385357
 
3.5%
288468
 
2.6%
0 252901
 
2.3%
1 77156
 
0.7%
2 39132
 
0.4%
5 38077
 
0.3%
( 30080
 
0.3%
) 30080
 
0.3%
Other values (30) 171277
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54085176
99.9%
None 62543
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9247406
17.1%
e 4528203
 
8.4%
t 3303096
 
6.1%
a 2847244
 
5.3%
i 2734409
 
5.1%
n 2612038
 
4.8%
r 2324317
 
4.3%
o 2270641
 
4.2%
s 2082270
 
3.8%
h 1882573
 
3.5%
Other values (73) 20252979
37.4%
None
ValueCountFrequency (%)
€ 19724
31.5%
â 19724
31.5%
™ 17883
28.6%
½ 993
 
1.6%
¿ 972
 
1.6%
ï 972
 
1.6%
 863
 
1.4%
œ 695
 
1.1%
  413
 
0.7%
˜ 205
 
0.3%
Other values (2) 99
 
0.2%

Interactions

2025-01-15T17:59:01.590801image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-15T17:58:59.348199image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-15T17:59:01.075780image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:59:02.063256image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:53.786407image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:54.674778image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:55.611606image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:56.632836image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:57.535461image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:58.434434image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:59.439691image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:59:00.299447image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-15T17:58:58.614991image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:59.618908image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:59:00.465008image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:59:01.332475image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:59:02.337226image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:54.046058image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:54.933619image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:55.984875image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:56.898014image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:57.798804image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:58.697283image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:59.706021image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:59:00.544860image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:59:01.419254image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:59:02.426770image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:54.129417image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:55.018101image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:56.069512image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:56.981573image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:57.884247image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:58.781541image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:58:59.793953image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:59:00.633384image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-15T17:59:01.497438image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Correlations

2025-01-15T17:59:16.748987image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
actual_weightdrawfinishing_positionhorse_numberrace_classrace_courserace_distancerace_numberrunning_position_1running_position_2running_position_3running_position_4running_position_5running_position_6tracktrack_condition
actual_weight1.0000.0040.037-0.8250.1210.0420.015-0.084-0.011-0.017-0.054-0.090-0.042-0.1010.0280.008
draw0.0041.0000.2690.0290.0000.1860.0510.0260.1380.1370.0940.0540.0430.0000.0430.000
finishing_position0.0370.2691.0000.0360.0000.0340.0080.0000.0820.1030.4580.7540.8190.9980.0000.000
horse_number-0.8250.0290.0361.0000.0000.1900.0100.0130.0780.0810.0910.0970.0730.0900.0410.000
race_class0.1210.0000.0000.0001.0000.1940.1970.3380.0000.0000.0000.0000.0000.0000.1280.052
race_course0.0420.1860.0340.1900.1941.0000.3850.2550.1810.1750.1460.0760.0000.0000.5360.161
race_distance0.0150.0510.0080.0100.1970.3851.0000.0760.0150.0190.0320.006-0.013-0.0660.1600.084
race_number-0.0840.0260.0000.0130.3380.2550.0761.0000.0220.0230.0230.007-0.0030.0150.0700.050
running_position_1-0.0110.1380.0820.0780.0000.1810.0150.0221.0000.9330.6300.3050.171-0.0560.0360.000
running_position_2-0.0170.1370.1030.0810.0000.1750.0190.0230.9331.0000.7130.3340.177-0.0660.0390.000
running_position_3-0.0540.0940.4580.0910.0000.1460.0320.0230.6300.7131.0000.4320.203-0.0790.0240.000
running_position_4-0.0900.0540.7540.0970.0000.0760.0060.0070.3050.3340.4321.0000.340-0.0220.0000.000
running_position_5-0.0420.0430.8190.0730.0000.000-0.013-0.0030.1710.1770.2030.3401.0000.2460.0000.000
running_position_6-0.1010.0000.9980.0900.0000.000-0.0660.015-0.056-0.066-0.079-0.0220.2461.0000.0000.000
track0.0280.0430.0000.0410.1280.5360.1600.0700.0360.0390.0240.0000.0000.0001.0000.227
track_condition0.0080.0000.0000.0000.0520.1610.0840.0500.0000.0000.0000.0000.0000.0000.2271.000

Missing values

2025-01-15T17:59:02.608581image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
A simple visualization of nullity by column.
2025-01-15T17:59:03.006564image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-01-15T17:59:03.278690image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

finishing_positionhorse_numberhorse_namehorse_idjockeytraineractual_weightdeclared_horse_weightdrawlength_behind_winnerrunning_position_1running_position_2running_position_3running_position_4finish_timewin_oddsrunning_position_5running_position_6race_idsrcrace_daterace_courserace_numberrace_classrace_distancetrack_conditionrace_nametracksectional_timeincident_report
0312.0CAREFREE LET GOT059M L YeungC S Shum1121060226.04.03.0NaN1.09.339.2NaNNaN2016-07020161001-6.html2016-10-01Sha Tin6Class 31200GOODSHANGHAI HANDICAPTURF - "A+3" COURSE23.70 22.34 22.98\n After beginning awkwardly and making contact with LUCKY GUY, ENDEARING then shifted in, resulting in CAPE THE FAITH which began awkwardly being further hampered.\nCALL ME AWESOME began awkwardly, shifted out and bumped the hindquarters of CAREFREE LET GO.\nOn the first turn at the 850 Metres, CALL ME AWESOME (K C Leung) shifted out, resulting in ORIONIDS being hampered and taken wider. K C Leung advised that CALL ME AWESOME then hung out throughout the middle stages and he was unable to get the horse to relax whilst racing in the lead. He said as a consequence CALL ME AWESOME was beaten soon after straightening and then weakened in the Straight. A veterinary inspection of CALL ME AWESOME immediately following the race did not show any significant findings.\nPassing the 500 Metres, LAUGH OUT LOUD was steadied when momentarily tightened for room between LOVELY DELOVELY and GORGEOUS KING which shifted out slightly.\nCAREFREE LET GO was held up for a short distance in the early part of the Straight.\nAlso in the early part of the Straight, LAUGH OUT LOUD was awkwardly placed outside the heels of GORGEOUS KING.\nWhen placed under pressure in the Straight, ORIONIDS raced greenly and was inclined to hang out.\nWhen questioned regarding his riding of ROUNDABOUT in the Home Straight, particularly in the early part of the Straight, D Whyte stated that after discussions with connections prior to its last start win, it was felt that ROUNDABOUT gives its best when able to be brought to the outside as the horse is reluctant to improve between runners. He said it was decided to ride ROUNDABOUT in exactly the same manner as its last start by going back from its outside barrier and bringing the horse to the extreme outside on straightening. He said on straightening he brought ROUNDABOUT to the outside and rode the horse in a hands and heels fashion in the early part of the Straight and similar to last start, the horse let down well and commenced to close off strongly. He said that he continued to ride ROUNDABOUT hands and heels before pulling the whip near the 150 Metres as ROUNDABOUT continued to close off well. D Whyte was advised that his explanation would be reported, however, he must ensure that he does not give his mounts too much to do.\nIRON BOY and LUCKY GUY were sent for sampling.\n
131.0VERY RICH MANV286U RispoliT K Ng133105793/41.01.03.0NaN1.10.5319NaNNaN2016-43820170222-3.html2017-02-22Happy Valley3Class 41200GOOD TO FIRMKWAI CHUNG HANDICAPTURF - "C+3" COURSE24.12 23.20 23.05\n KWAICHUNG BROTHERS was slow to begin.\nGOLDEN ACHIEVER shifted in at the start and bumped AH BO.\nROCKET LET WIN began only fairly and then shortly after the start was steadied when crowded for room inside VERY RICH MAN which shifted in.\nG-ONE LOVER shifted in at the start and bumped GAME OF FUN.\nFrom the outside barrier, BRIGHT STAR got its head up when being steadied to be shifted across behind runners in the early stages.\nCONTRIBUTION lost its right hind plate after the 900 Metres.\nApproaching and passing the 500 Metres, AH BO got its head on the side and lay out.\nFor the majority of the race, ROCKET LET WIN travelled wide and without cover.\nThe Stewards deferred the declaration of weighed-in as they were of the prima facie view that an incident had occurred approaching the 200 Metres which cast sufficient doubt on whether DR RACE (B Prebble) should be declared the 5th placegetter. When N Callan, the rider of the 6th placegetter, GOLDEN ACHIEVER, did not enter a formal protest/objection on behalf of the connections of GOLDEN ACHIEVER, the Stewards believed that it was appropriate for the matter to proceed to a formal/objection hearing. Whilst these placings did not affect betting, it was relevant that there was the issue of prizemoney in respect of the 5th placegetter. After taking evidence from B Prebble, Mr S K Sit, assistant trainer allocated to Mr D E Ferraris, the trainer of DR RACE, and N Callan, it was found that approaching the 200 Metres DR RACE was shifted to the outside of GAME OF FUN to obtain clear running which resulted in GOLDEN ACHIEVER being checked and losing its rightful running when crowded for room inside CONTRIBUTION. Having regard to the neck margin between both horses at the end of the race and the manner in which they were finishing off the race, the Stewards were satisfied that had the interference not occurred GOLDEN ACHIEVER would have finished in front of DR RACE. Accordingly, the protest/objection was sustained and the placings amended to read No. 3, GAME OF FUN, 1st; No. 11, CONTRIBUTION, 2nd; No. 1, VERY RICH MAN, 3rd; No. 9, G-ONE LOVER, 4th; No. 2, GOLDEN ACHIEVER, 5th; and No. 4, DR RACE, 6th. N Callan was advised that in similar circumstances he must be aware of the placings of horses and to ensure that he has the interests of connections in mind. At a subsequent inquiry, B Prebble pleaded guilty to a charge of careless riding [Rule 100(1)] and was suspended from riding in races for a period to commence on Wednesday, 8 March 2017 and to expire on Monday, 13 March 2017 on which day he may resume race riding (2 Hong Kong racedays). In assessing penalty, the Stewards took into account Jockey Prebble’s good race riding record.\nG-ONE LOVER, GAME OF FUN and CONTRIBUTION were sent for sampling.\n
2124.0FANTASTIC KAKAP363B PrebbleL Ho125112517-1/43.04.05.012.01.36.1319NaNNaN2015-24920151213-6.html2015-12-13Sha Tin6Class 21600GOODEISHIN PRESTON HANDICAPTURF - "A" COURSE24.55 23.86 24.20 22.35\n PHOTON WILLIE was crowded for room on jumping between TRAVEL FIRST and PIKACHU which got its head on the side and shifted in despite the efforts of its rider.\nAPOLLO'S CHOICE, which began awkwardly, and WAH MAY FRIEND bumped at the start.\nAs the start was effected, REGENCY KING lifted its front feet off the ground and then from a wide barrier was shifted across behind runners in the early stages.\nAlso from the outside barrier, WINNING LEADER was taken across behind runners in the early stages.\nFor some distance after the 700 Metres, APOLLO'S CHOICE was awkwardly placed close to the heels of FANTASTIC KAKA.\nPassing the 350 Metres, WAH MAY FRIEND was awkwardly placed close to the heels of BRILLIANT SHINE after being initially disappointed for running outside that horse. PHOTON WILLIE, which was following, was shifted in away from the heels of WAH MAY FRIEND in consequence.\nApproaching the 300 Metres, SICHUAN DAR and REGENCY KING made contact as SICHUAN DAR improved into tight running outside WINNING LEADER. Then passing the 300 Metres, SICHUAN DAR was awkwardly placed outside the heels of WINNING LEADER when that horse was taken out by VICTORY MAGIC which was taken wider by ISHVARA.\nPassing the 300 Metres, PIKACHU was shifted in away from the heels of FANTASTIC KAKA which was giving ground in order to obtain clear running.\nThroughout the race, BRILLIANT SHINE travelled wide and without cover.\nThe Stewards interviewed M Demuro regarding his riding out of WAH MAY FRIEND over the concluding stages. M Demuro was advised that as the Stewards could not be satisfied to the requisite degree that WAH MAY FRIEND would have finished in front of TRAVEL FIRST, having in mind that he stopped riding his horse over about the final two strides and also having regard to the neck margin between the horses at the end of the race, nonetheless he was severely reprimanded and advised to ensure that he rides his mounts out all the way to the end of the race where circumstances permit. \nAfter the race, B Prebble (FANTASTIC KAKA) reported that the horse did not feel comfortable in its action over the latter stages of the race. A veterinary inspection of FANTASTIC KAKA immediately following the race did not show any significant findings. Before being allowed to race again, FANTASTIC KAKA will be subjected to an official veterinary examination.\nA veterinary inspection of PHOTON WILLIE and BRILLIANT DREAM immediately following the race did not show any significant findings.\nVICTORY MAGIC, WERTHER and APOLLO'S CHOICE were sent for sampling.\n
376.0VICTORY MAGICT272J MoreiraJ Moore122115413-1/26.04.07.0NaN1.11.7713NaNNaN2014-64320150524-10.html2015-05-24Sha Tin10Class 21200YIELDINGSTAUNTON HANDICAPTURF - "C+3" COURSE23.84 23.09 24.27\n DEEP THINKER was checked when crowded for room on jumping between IMPERIAL CHAMPION and OUR FOLKS which shifted out.\nCLEVER BEAVER shifted out abruptly at the start, resulting in IMPERIAL ROME being crowded for room out onto DILLY which became unbalanced after being bumped by IMPERIAL ROME.\nMR GENUINE began awkwardly, shifted out and bumped the hindquarters of GOLDEN DEER, causing both horses to become unbalanced. After this, MR GENUINE and GOLDEN DEER were shifted across behind runners.\nNear the 1150 Metres, DINING WORLD was hampered and lost ground when crowded for room inside OUR FOLKS (Apprentice H N Wong) which shifted in. Apprentice Wong was severely reprimanded and advised that in similar circumstances he would be expected to make every endeavour to prevent his mounts from shifting ground.\nNear the 600 Metres, MR GENUINE was steadied away from the heels of OUR FOLKS.\nRounding the Home Turn, MR GENUINE raced in restricted room between OUR FOLKS and DEEP THINKER which shifted out.\nAt the entrance to the Straight, DEEP THINKER was shifted to the inside of VICTORY MAGIC to obtain clear running.\nPassing the 350 Metres, MR GENUINE was steadied and shifted to the outside of VICTORY MAGIC.\nPassing the 200 Metres, VICTORY MAGIC was shifted out away from the heels of DEEP THINKER which shifted to the outside of ALL GREAT FRIENDS.\nNear the 150 Metres, J Moreira (VICTORY MAGIC) momentarily lost the use of his whip.\nAfter the race, D Whyte stated that DINING WORLD did not stretch out on today’s track at any stage of the race and never travelled comfortably. A veterinary inspection of DINING WORLD immediately following the race did not show any significant findings.\nA veterinary inspection of DILLY immediately following the race did not show any significant findings.\nDEEP THINKER and STRATHMORE were sent for sampling.\n
4104.0EXCITING DREAMP191H BowmanJ Moore127107914-3/45.05.05.010.01.23.0214NaNNaN2015-25220151213-9.html2015-12-13Sha Tin9Class 11400GOODFLYING DANCER HANDICAPTURF - "A" COURSE13.56 22.61 24.02 22.06\n DIVINE CALLING was withdrawn on 12.12.15 by order of the Stewards acting on veterinary advice (inappetence) and was replaced by Standby Declared Starter KABAYAN (U Rispoli). Before being allowed to race again, DIVINE CALLING will be subjected to an official veterinary examination.\nKABAYAN was slow to begin.\nLUCKY BUBBLES began awkwardly.\nPACKING LLAREGYB began only fairly.\nSUN JEWELLERY and SUPER LIFELINE bumped at the start.\nFrom a wide barrier, I'M IN CHARGE got its head up on a number of occasions when being steadied to be taken across behind runners in the early stages.\nMaking the turn after the 900 Metres, KABAYAN commenced to travel keenly and shifted out away from the heels of I'M IN CHARGE which was awkwardly placed close to the heels of GURUS DREAM. After this, KABAYAN travelled wide and without cover.\nWhen questioned regarding his riding of PACKING LLAREGYB in the early part of the Straight, M Demuro stated that his mount was unbalanced after making the Home Turn and was inclined to get its head on the side and lay in. He said he took some time to balance the horse before being able to place it under pressure prior to the 300 Metres. He said after this PACKING LLAREGYB finished off the race fairly.\nA veterinary inspection of I'M IN CHARGE and EXCITING DREAM immediately following the race did not show any significant findings.\nSUN JEWELLERY and MULTIVICTORY were sent for sampling.\n
593.0WINNAMP119G MosseT P Yung132118166-3/412.012.012.09.01.35.5921NaNNaN2015-30020160101-10.html2016-01-01Sha Tin10Class 31600GOODKOWLOON PEAK HANDICAPTURF - "B+2" COURSE24.09 22.14 24.40 23.88\n APPROVE began awkwardly.\nTRAVEL AMBASSADOR was slow to begin.\nJOLLY JOLLY began only fairly and was ridden along in the early stages to make up lost ground.\nFrom wide barriers, GOOD CHOICE and VICTORY MASTER were shifted across behind runners in the early stages.\nAt the 1500 Metres, EASTERN EXPRESS and HAPPY AGILITY bumped.\nNear the 1300 Metres, HAPPY AGILITY was awkwardly placed close to the heels of GRAND HARBOUR.\nAgain making the turn after the 900 Metres, HAPPY AGILITY was steadied away from the heels of GRAND HARBOUR which got its head up when racing close to the heels of APPROVE. After this, HAPPY AGILITY continued to prove very difficult to settle and shifted out away from the heels of GRAND HARBOUR, resulting in EASTERN EXPRESS being taken wider.\nPassing the 800 Metres, EASTERN EXPRESS was steadied to obtain a position with cover behind HAPPY AGILITY.\nKIRAM had difficulty obtaining clear running until after the 300 Metres.\nPassing the 300 Metres, GOOD CHOICE raced in restricted room between TRAVEL AMBASSADOR and GRAND HARBOUR which lay in under pressure. GOOD CHOICE then had difficulty obtaining clear running approaching the 200 Metres when improving into tight running between CHEERFUL BOY and GRAND HARBOUR.\nApproaching the 100 Metres, GRAND HARBOUR was momentarily steadied away from the heels of THE SHOW.\nThroughout the race, THE SHOW travelled wide and without cover.\nThe performance of APPROVE, which gave ground abruptly in the Straight and subsequently finished tailed out, was considered unacceptable. Before being allowed to race again, APPROVE will be required to perform to the satisfaction of the Stewards in a barrier trial and be subjected to an official veterinary examination.\nA veterinary inspection of APPROVE and JOLLY JOLLY immediately following the race did not show any significant findings.\nJOLLY JOLLY, GONNA RUN and KIRAM were sent for sampling.\n
632.0GREAT SKYN426N CallanA T Millard13111841027.06.03.0NaN1.09.669.4NaNNaN2014-03120140924-3.html2014-09-24Sha Tin3Class 31200GOODLEK YUEN HANDICAPALL WEATHER TRACK23.77 22.86 22.71\n As the start was effected, SIGHT BELIEVER lifted its front feet off the ground and consequently began only fairly. Then a short distance after the start, SIGHT BELIEVER was steadied away from the heels of CHEETAH BOY which shifted out.\nWINNING INSTINCT shifted out at the start, resulting in CAGA FORCE being hampered.\nALL WIN BOY was tardy to begin.\nAfter the 600 Metres, SIGHT BELIEVER was awkwardly placed close to the heels of EN CIVIL.\nRounding the Home Turn, GREAT SKY and CHEETAH BOY raced tight due to CHEETAH BOY shifting out to obtain clear running.\nIn the Straight, CHEETAH BOY got its head on the side and lay out under pressure, resulting in GREAT SKY being inconvenienced in the early part of the Straight and again near the 100 Metres.\nThroughout the race, RUMBA KING travelled wide and without cover.\nAfter the race, D Whyte reported that he was unable to offer any explanation for the disappointing performance of CAGA FORCE. He said the horse travelled satisfactorily in the early and middle stages, however, after coming under pressure near the 400 Metres was most disappointing in the manner in which it weakened out of the race in the Straight. Mr C S Shum, the trainer of CAGA FORCE, was unable to offer any explanation for the horse's disappointing performance other than it may not have been suited by the addition of blinkers. He said he had studied the videos of CAGA FORCE, which was having its first start for his stable tonight, and he was of the belief that the horse was not finishing off its races. He said it was for this reason that he applied blinkers to the horse. He said CAGA FORCE's track work in this piece of gear had indicated that it would benefit from wearing it, however, in tonight's race, he felt the horse was inclined to race too keenly with the blinkers and therefore he would consider altering the horse's gear in its future starts. A veterinary inspection of CAGA FORCE immediately following the race did not show any significant findings. The performance of CAGA FORCE was considered unacceptable. Before being allowed to race again, CAGA FORCE will be required to perform to the satisfaction of the Stewards in an official barrier trial and be subjected to an official veterinary examination.\nA veterinary inspection of SIGHT BELIEVER immediately following the race did not show any significant findings.\nRUMBA KING and WINNING INSTINCT were sent for sampling.\n
793.0COUNTRY MELODYT011B PrebbleJ Size1311104435.06.09.0NaN0.56.6842NaNNaN2016-11120161016-10.html2016-10-16Sha Tin10Class 21000GOOD TO FIRMTAILORBIRD HANDICAPTURF - "C" COURSE12.98 20.81 22.41\n Just prior to the start being effected, ARCHIPPUS became fractious and then was slow to begin.\nShortly after the start, RACING SUPERNOVA was crowded for room between HAPPY YEAH YEAH and MY LITTLE FRIEND which shifted out. The tightening to RACING SUPERNOVA was exacerbated when HAPPY YEAH YEAH shifted in when bumped on the hindquarters by RACING SUPERNOVA. This resulted in RACING SUPERNOVA losing ground and racing towards the rear of the field.\nApproaching the 800 Metres, RACING SUPERNOVA momentarily raced in restricted room between HAPPY YEAH YEAH and MY LITTLE FRIEND which got its head on the side and shifted out despite the efforts of its rider.\nPassing the 400 Metres, RACING SUPERNOVA was shifted to the outside of MALMSTEEN after being disappointed for running between that horse and COUNTRY MELODY.\nARCHIPPUS was unable to obtain clear running until over the final 300 Metres and consequently was not able to be tested.\nPassing the 200 Metres, SMART DECLARATION was crowded for room between GOLDEN HARVEST and TRIUMPHANT JEWEL which shifted out marginally.\nPassing the 100 Metres, RACING SUPERNOVA raced tight between CHARITY JOY and HELLA HEDGE which was racing tight outside BAD BOY.\nOver the concluding stages, RACING SUPERNOVA raced close to the heels of ADVENTURER.\nRACING SUPERNOVA, ADVENTURER and BAD BOY were sent for sampling.\n
8814.0PERFECT TIMINGT019M ChadwickT P Yung1131112113-1/214.014.011.08.01.36.3159NaNNaN2016-46320170305-2.html2017-03-05Sha Tin2Class 51600GOOD TO FIRMLOTUS BRIDGE HANDICAPTURF - "C" COURSE24.31 22.64 24.68 24.13\n STORM KID began awkwardly and lost ground.\nPOLYMER LUCK shifted out at the start and bumped SPICY DOUBLE.\nHAR HAR CHARMING began only fairly.\nAfter travelling a short distance, RED HORSE shifted out and bumped the hindquarters of AUDACITY which became unbalanced.\nApproaching the 1500 Metres, MY FOLKS was awkwardly placed inside the heels of STRIKING STAR.\nApproaching and passing the 1400 Metres, STRIKING STAR got its head up when travelling keenly.\nU Rispoli (HAR HAR CHARMING) pleaded guilty to a charge of careless riding [Rule 100(1)] in that approaching the 1200 Metres he permitted his mount to shift in when not clear of FORTUNE GIGGLES, resulting in that horse being taken in onto STRIKING STAR which in turn was taken in onto MY FOLKS, causing that horse to be crowded for room and checked. U Rispoli was suspended from riding in races for a period to commence on Sunday, 12 March 2017 and to expire on Thursday, 16 March 2017 on which day he may resume race riding (2 Hong Kong racedays). In assessing penalty, the Stewards took into account Jockey Rispoli's good race riding record.\nAfter the 1100 Metres, POLYMER LUCK proved difficult to settle and got its head up for some distance when racing without cover.\nPassing the 900 Metres, AUDACITY was crowded for room between POLYMER LUCK and DASHING DART which shifted out away from the heels of MY FOLKS.\nPassing the 600 Metres, POLYMER LUCK was checked when proving difficult to settle and awkwardly placed behind RED HORSE.\nAlso passing the 600 Metres, SPICY DOUBLE proved difficult to settle and was checked out away from the heels of DASHING DART.\nNear the 300 Metres, DASHING DART was shifted to the outside of RED HORSE after being disappointed for running between that horse and EMPIRE OF MONGOLIA. When being shifted out further to obtain clear running, DASHING DART was awkwardly placed close to the heels of POLYMER LUCK a short distance later.\nApproaching the 200 Metres, SPICY DOUBLE was crowded for room inside AUDACITY by PERFECT TIMING (M Chadwick) which shifted out to obtain clear running. M Chadwick was advised to exercise more care.\nNear the 50 Metres, RED HORSE lay in under pressure. \nThroughout the race, HAR HAR CHARMING travelled wide and without cover and in the Straight gave ground. A veterinary inspection of HAR HAR CHARMING immediately following the race did not show any significant findings. The performance of HAR HAR CHARMING, which finished tailed out, was considered unacceptable. Before being allowed to race again, HAR HAR CHARMING will be required to perform to the satisfaction of the Stewards in a barrier trial and be subjected to an official veterinary examination.\nDASHING DART and POLYMER LUCK were sent for sampling.\n
9102.0TWIN DELIGHTS125Z PurtonC Fownes13310881454.02.02.010.01.37.9237NaNNaN2015-18720151118-8.html2015-11-18Sha Tin8Class 21650GOODSUTHERLAND HANDICAPALL WEATHER TRACK27.46 22.31 23.71 23.66\n From a wide barrier, GOLDLAND DANCER was shifted across behind runners in the early stages.\nHIGH AND MIGHTY lost its left front plate in the early stages.\nApproaching the 1200 Metres, MAJESTIC ANTHEM momentarily raced tight inside WINNIE'S HORSE which got its head on the side and shifted in away from OBLITERATOR.\nApproaching the 1000 Metres, MAJESTIC ANTHEM was again crowded for room inside WINNIE'S HORSE which was racing tight inside OBLITERATOR (N Callan). N Callan was advised to ensure that he leaves sufficient racing room for runners to his inside in future.\nAfter the 900 Metres, GOAL FOR GOLD was left racing wide and without cover.\nGOODHEART SUCCESS lost its left front plate whilst MAJESTIC ANTHEM lost its right front plate in the middle stages.\nPassing the 200 Metres, GOAL FOR GOLD was steadied when awkwardly placed outside the heels of CHOICE TREASURE which was taken out by OBLITERATOR which shifted ground when tiring.\nFor a short distance near the 100 Metres, GOODHEART SUCCESS had some difficulty obtaining clear running.\nA veterinary inspection of OBLITERATOR immediately following the race did not show any significant findings.\nMAJESTIC ANTHEM and HIGH AND MIGHTY were sent for sampling.\n<19/11/2015 Additional Veterinary Report>The Clinical Veterinary Surgeon reported that BULLISH BOY was lame in its left front leg on the morning after racing. Before being allowed to race again, BULLISH BOY will be subjected to an official veterinary examination.\n
finishing_positionhorse_numberhorse_namehorse_idjockeytraineractual_weightdeclared_horse_weightdrawlength_behind_winnerrunning_position_1running_position_2running_position_3running_position_4finish_timewin_oddsrunning_position_5running_position_6race_idsrcrace_daterace_courserace_numberrace_classrace_distancetrack_conditionrace_nametracksectional_timeincident_report
2231414.0COBY BOYA297M L YeungT P Yung12411516-8.07.05.01.01.21.4198NaNNaN2016-78820170709-10.html2017-07-09Sha Tin10Class 31400GOODLEI YUE MUN PARK HANDICAPTURF - "B+2" COURSE13.29 21.64 22.98 23.50\n RADIANT BUNNY was withdrawn on 8.7.17 by order of the Stewards acting on veterinary advice (lame right fore) and was replaced by Standby Declared Starter LUCKY GUY (N Callan). Before being allowed to race again, RADIANT BUNNY will be subjected to an official veterinary examination.\nC Y Ho (ALCAZAR) was fined the sum of $2,000 for presenting himself to be weighed out with the incorrect saddle cloth number.\nMAGIC AGILITY was slow to begin.\nREGENCY BO BO shifted in at the start, resulting in DEJA VU being crowded for room between that horse and STARLIT KNIGHT. In this incident, STARLIT KNIGHT became unbalanced when bumped by DEJA VU.\nCOBY BOY shifted out at the start and inconvenienced GRANITE BELT.\nWhen being steadied from a wide barrier shortly after the start, ALCAZAR got its head up.\nFrom wide barriers, GIANT TURTLE and IRON BOY were shifted across behind runners in the early stages.\nApproaching the 1100 Metres, LUCKY GUY was awkwardly placed close to the heels of STARLIT KNIGHT which shifted out.\nPassing the 400 Metres, DEJA VU was shifted out in an attempt to improve between PRESIDENTPARAMOUNT and COBY BOY and in doing so bumped the hindquarters of COBY BOY, resulting in that horse becoming unbalanced and shifting in. DEJA VU was consequently disappointed for running between those horses and approaching the 300 Metres was shifted to the outside of COBY BOY.\nApproaching the 200 Metres, FLYING MONKEY was hampered when disappointed for running between SIR REDALOT and REGENCY BO BO, both of which shifted slight ground.\nPassing the 100 Metres, DEJA VU was awkwardly placed behind COBY BOY when racing tight inside LUCKY GUY.\nThroughout the race, PRESIDENTPARAMOUNT travelled wide and without cover.\nThe performances of MAGIC AGILITY and ALCAZAR, which finished tailed out, were considered unacceptable. Before being allowed to race again, MAGIC AGILITY and ALCAZAR will be required to perform to the satisfaction of the Stewards in a barrier trial and be subjected to an official veterinary examination.\nAfter the race, J Moreira stated that he had to make too much use of SIR REDALOT in the early stages to cross to the lead and consequently the horse was then not able to finish off the race strongly. A veterinary inspection of SIR REDALOT immediately following the race did not show any significant findings.\nREGENCY BO BO, COBY BOY and LUCKY GUY were sent for sampling.\n
223151311.0MAGIC AGILITYA233H T MoL Ho1111052821-3/412.013.014.013.01.24.8899NaNNaN2016-78820170709-10.html2017-07-09Sha Tin10Class 31400GOODLEI YUE MUN PARK HANDICAPTURF - "B+2" COURSE13.29 21.64 22.98 23.50\n RADIANT BUNNY was withdrawn on 8.7.17 by order of the Stewards acting on veterinary advice (lame right fore) and was replaced by Standby Declared Starter LUCKY GUY (N Callan). Before being allowed to race again, RADIANT BUNNY will be subjected to an official veterinary examination.\nC Y Ho (ALCAZAR) was fined the sum of $2,000 for presenting himself to be weighed out with the incorrect saddle cloth number.\nMAGIC AGILITY was slow to begin.\nREGENCY BO BO shifted in at the start, resulting in DEJA VU being crowded for room between that horse and STARLIT KNIGHT. In this incident, STARLIT KNIGHT became unbalanced when bumped by DEJA VU.\nCOBY BOY shifted out at the start and inconvenienced GRANITE BELT.\nWhen being steadied from a wide barrier shortly after the start, ALCAZAR got its head up.\nFrom wide barriers, GIANT TURTLE and IRON BOY were shifted across behind runners in the early stages.\nApproaching the 1100 Metres, LUCKY GUY was awkwardly placed close to the heels of STARLIT KNIGHT which shifted out.\nPassing the 400 Metres, DEJA VU was shifted out in an attempt to improve between PRESIDENTPARAMOUNT and COBY BOY and in doing so bumped the hindquarters of COBY BOY, resulting in that horse becoming unbalanced and shifting in. DEJA VU was consequently disappointed for running between those horses and approaching the 300 Metres was shifted to the outside of COBY BOY.\nApproaching the 200 Metres, FLYING MONKEY was hampered when disappointed for running between SIR REDALOT and REGENCY BO BO, both of which shifted slight ground.\nPassing the 100 Metres, DEJA VU was awkwardly placed behind COBY BOY when racing tight inside LUCKY GUY.\nThroughout the race, PRESIDENTPARAMOUNT travelled wide and without cover.\nThe performances of MAGIC AGILITY and ALCAZAR, which finished tailed out, were considered unacceptable. Before being allowed to race again, MAGIC AGILITY and ALCAZAR will be required to perform to the satisfaction of the Stewards in a barrier trial and be subjected to an official veterinary examination.\nAfter the race, J Moreira stated that he had to make too much use of SIR REDALOT in the early stages to cross to the lead and consequently the horse was then not able to finish off the race strongly. A veterinary inspection of SIR REDALOT immediately following the race did not show any significant findings.\nREGENCY BO BO, COBY BOY and LUCKY GUY were sent for sampling.\n
22316105.0A STAR LUSTERA259K C NgK L Man1241133105-3/412.010.010.0NaN0.58.2899NaNNaN2016-78920170712-1.html2017-07-12Happy Valley1Class 41000GOOD TO FIRMBULLDOZER HANDICAPTURF - "A" COURSE12.57 21.25 23.54\n A STAR LUSTER began awkwardly and lost ground and then raced greenly throughout the event.\nDR RACE was slow to begin and then was hampered by TRENDIFUL which was taken out by YOU KNOW WHO which, after beginning awkwardly, got its head on the side and shifted out further despite the efforts of its rider.\nRUGBY DIAMOND shifted out on jumping and hampered TRIUMPHAL TRUMPET.\nFrom the outside barrier, SNOW HAWK was steadied in the early stages and shifted across behind runners.\nIn the early and middle stages, TRIUMPHAL TRUMPET raced greenly.\nC Murray (DOUBLE MASTER) pleaded guilty to a charge of careless riding [Rule 100(1)] in that near the 850 Metres he permitted his mount to shift in when not clear of ACCESSION YEARS, causing that horse to be hampered and taken in and ultimately to be steadied away from the heels of DOUBLE MASTER. C Murray was suspended from riding in races for a period to commence on Monday, 17 July 2017 and to expire on Thursday, 27 July 2017 on which day he may resume race riding.\nApproaching the 800 Metres, TRENDIFUL was momentarily awkwardly placed close to the heels of DOUBLE MASTER.\nPassing the 800 Metres, SILVER SPUN was steadied away from the heels of RUGBY DIAMOND (C Schofield) which shifted in when not properly clear. C Schofield was severely reprimanded and advised to ensure that he is properly clear when shifting ground in similar circumstances.\nAfter the 800 Metres, ACCESSION YEARS was left racing wide and without cover and making the turn near the 550 Metres got its head on the side, lay in and brushed TRENDIFUL which became unbalanced. TRENDIFUL then hung out, resulting in ACCESSION YEARS being taken wider and both horses then racing wide and without cover.\nAlso making the turn near the 550 Metres, SILVER SPUN became unbalanced after being bumped by OCEAN ROAR which made the turn awkwardly.\nNear the 450 Metres, CALIFORNIA ASPAR was awkwardly placed close to the heels of OCEAN ROAR when racing tight inside DOUBLE MASTER.\nPassing the 200 Metres, DR RACE drifted out under pressure.\nA veterinary inspection of OCEAN ROAR immediately following the race including an endoscopic examination showed a substantial amount of mucus in the horse’s trachea.\nDR RACE, SILVER SPUN and CALIFORNIA ASPAR were sent for sampling.\n
22317126.0SNOW HAWKA289C Y HoC Fownes12510261211-1/210.012.012.0NaN0.59.2299NaNNaN2016-78920170712-1.html2017-07-12Happy Valley1Class 41000GOOD TO FIRMBULLDOZER HANDICAPTURF - "A" COURSE12.57 21.25 23.54\n A STAR LUSTER began awkwardly and lost ground and then raced greenly throughout the event.\nDR RACE was slow to begin and then was hampered by TRENDIFUL which was taken out by YOU KNOW WHO which, after beginning awkwardly, got its head on the side and shifted out further despite the efforts of its rider.\nRUGBY DIAMOND shifted out on jumping and hampered TRIUMPHAL TRUMPET.\nFrom the outside barrier, SNOW HAWK was steadied in the early stages and shifted across behind runners.\nIn the early and middle stages, TRIUMPHAL TRUMPET raced greenly.\nC Murray (DOUBLE MASTER) pleaded guilty to a charge of careless riding [Rule 100(1)] in that near the 850 Metres he permitted his mount to shift in when not clear of ACCESSION YEARS, causing that horse to be hampered and taken in and ultimately to be steadied away from the heels of DOUBLE MASTER. C Murray was suspended from riding in races for a period to commence on Monday, 17 July 2017 and to expire on Thursday, 27 July 2017 on which day he may resume race riding.\nApproaching the 800 Metres, TRENDIFUL was momentarily awkwardly placed close to the heels of DOUBLE MASTER.\nPassing the 800 Metres, SILVER SPUN was steadied away from the heels of RUGBY DIAMOND (C Schofield) which shifted in when not properly clear. C Schofield was severely reprimanded and advised to ensure that he is properly clear when shifting ground in similar circumstances.\nAfter the 800 Metres, ACCESSION YEARS was left racing wide and without cover and making the turn near the 550 Metres got its head on the side, lay in and brushed TRENDIFUL which became unbalanced. TRENDIFUL then hung out, resulting in ACCESSION YEARS being taken wider and both horses then racing wide and without cover.\nAlso making the turn near the 550 Metres, SILVER SPUN became unbalanced after being bumped by OCEAN ROAR which made the turn awkwardly.\nNear the 450 Metres, CALIFORNIA ASPAR was awkwardly placed close to the heels of OCEAN ROAR when racing tight inside DOUBLE MASTER.\nPassing the 200 Metres, DR RACE drifted out under pressure.\nA veterinary inspection of OCEAN ROAR immediately following the race including an endoscopic examination showed a substantial amount of mucus in the horse’s trachea.\nDR RACE, SILVER SPUN and CALIFORNIA ASPAR were sent for sampling.\n
22318113.0BIG TIME BABYA157C MurrayK L Man13111095510.010.011.0NaN0.57.9099NaNNaN2016-79320170712-5.html2017-07-12Happy Valley5Class 31000GOOD TO FIRMLET ME FIGHT HANDICAPTURF - "A" COURSE12.67 20.97 23.44\n TRAVEL COMFORTS was withdrawn on 10.7.17 by order of the Stewards acting on veterinary advice (lame left hind) and was replaced by Standby Declared Starter ALL MY GAIN. Before being allowed to race again, TRAVEL COMFORTS will be subjected to an official veterinary examination. \nRACING MATE and BIG TIME BABY began only fairly and shortly after the start were crowded for room outside SWEETIE BARLEY which shifted out.\nTRIUMPHANT JEWEL and MOST BEAUTIFUL bumped at the start.\nFrom a wide barrier, ALL MY GAIN was shifted across behind runners in the early stages.\nPassing the 950 Metres, BEAUTY MASTER shifted out abruptly.\nApproaching the 900 Metres, MONEY BOY shifted in and bumped the hindquarters of WHO ELSE BUT YOU.\nBIG TIME BABY lost its left front plate passing the 800 Metres.\nMaking the turn near the 550 Metres, BEAUTY MASTER got its head on the side and lay out.\nWhen questioned, K Teetan (ACE KING) stated that he was instructed to attempt to lead if ACE KING began well having regard to the horse’s prior history of being fractious in the barriers. He said he was also told that if ACE KING did not show sufficient early speed to lead, it was acceptable for him to take a position with cover behind the leaders. He said, as is often the case, ACE KING was fractious in the barriers and reared and then as the start was effected began only fairly. He said as there were a number of horses, which were drawn better than ACE KING, being vigorously ridden to obtain forward positions, he did not believe that ACE KING would have sufficient early speed to be able to lead, therefore he elected to shift the horse across and obtain cover albeit further back in the field than had been intended.\nTRIUMPHANT JEWEL and MONEY BOY were sent for sampling.\n
2231917.0SOUTHERN LEGENDA252K TeetanC Fownes118112212-8.08.01.0NaN1.09.5518NaNNaN2016-79620170712-8.html2017-07-12Happy Valley8Class 21200GOOD TO FIRMSWEET ORANGE HANDICAPTURF - "A" COURSE23.51 22.62 23.42\n DRAGON GENERAL was slow to begin.\nFrom a wide barrier, SUPER TURBO was steadied in the early stages and shifted across behind runners.\nNear the 1150 Metres, COUNTRY MELODY and VERBINSKY were crowded for room inside HIGH FIVE (C Murray) which shifted in before being directed back out to relieve the tightening to runners on its inside. C Murray was advised to exercise more care when shifting ground.\nThroughout the race, FLYING TOURBILLON travelled wide and without cover.\nA veterinary inspection of RACING SUPERNOVA, HOUSE OF FUN and DRAGON GENERAL immediately following the race did not show any significant findings.\nSOUTHERN LEGEND and SUPER TURBO were sent for sampling.\n
22320145.0CHIMBORAAV411A SannaK W Lui1201214932-1/213.014.014.014.01.28.1597NaNNaN2016-80720170716-11.html2017-07-16Sha Tin11Class 21400GOOD TO YIELDINGTHE HONG KONG RACEHORSE OWNERS ASSOCIATION TROPHY (HANDICAP)TURF - "C" COURSE13.23 21.90 24.15 23.65\n MONGOLIAN KING was slow to begin.\nPIKACHU began very awkwardly and lost ground.\nCHIMBORAA shifted out at the start and bumped DUKEDOM. DUKEDOM was then crowded for room between CHIMBORAA and BULB ELITE.\nHEALTHY JOYFUL shifted in at the start and bumped MIDNIGHT RATTLER.\nFrom wide barriers, DUKEDOM and CIRCUIT HASSLER were shifted across behind runners in the early stages.\nWhen being steadied to obtain cover, BULB ELITE proved difficult to settle in the early stages.\nPassing the 800 Metres, CIRCUIT HASSLER shifted out abruptly away from the heels of SICHUAN DAR.\nAlso passing the 800 Metres, TURF SPRINT was awkwardly placed close to the heels of SOLAR HEI HEI.\nNear the 550 Metres, BIG BANG BONG got its head up when awkwardly placed behind of HEALTHY JOYFUL.\nTURF SPRINT lay out making the Home Turn.\nApproaching the 150 Metres, BIG BANG BONG and TURF SPRINT bumped.\nFor the majority of the race, DRAGON MASTER travelled wide and without cover.\nAfter the race, A Sanna stated that CHIMBORAA did not travel comfortably at any stage of the race and despite being ridden along after the 1000 Metres became detached from the field. A veterinary inspection of CHIMBORAA immediately following the race did not show any significant findings. The performance of CHIMBORAA, which finished tailed out, was considered unacceptable. Before being allowed to race again, CHIMBORAA will be required to perform to the satisfaction of the Stewards in a barrier trial and be subjected to an official veterinary examination.\nMONGOLIAN KING, SOLAR HEI HEI and BABA MAMA were sent for sampling.\n
22321118.0SO GENEROUSV402A SannaC H Yip1259756810.011.011.0NaN1.11.3599NaNNaN2016-79920170716-3.html2017-07-16Sha Tin3Class 41200GOODBIG PROFIT HANDICAPTURF - "C" COURSE23.54 22.53 24.01\n VERY RICH MAN was withdrawn on 15.7.17 by order of the Stewards acting on veterinary advice (lame right fore) and was replaced by first Standby Declared Starter JOLLY BOUNTIFUL (J Moreira). AIMING HIGH was also withdrawn on 15.7.17 by order of the Stewards acting on veterinary advice (lame right fore) and was replaced by second Standby Declared Starter RICHCITY FORTUNE (B Prebble). Before being allowed to race again, VERY RICH MAN and AIMING HIGH will be subjected to an official veterinary examination.\nSO GENEROUS began only fairly.\nFrom the outside barriers, GREAT TOPLIGHT and MY GIFT were steadied and shifted across behind runners in the early stages.\nNear the 750 Metres, JOLLY BOUNTIFUL was awkwardly placed close to the heels of OUR FOLKS.\nPassing the 400 Metres, JOLLY BOUNTIFUL was directed in from behind PHANTOM FALCON and OUR FOLKS to obtain clear running.\nJOLLY BOUNTIFUL had difficulty obtaining clear running from passing the 200 Metres and approaching the 150 Metres was shifted out away from the heels of RUMINARE. JOLLY BOUNTIFUL was then badly held up when disappointed for running between RUMINARE and RICHCITY FORTUNE. Then passing the 100 Metres, JOLLY BOUNTIFUL was shifted to the outside of RICHCITY FORTUNE to obtain clear running.\nJOLLY BOUNTIFUL, OUR FOLKS and PHANTOM FALCON were sent for sampling.\n
22322111.0CALCULATIONA248J MoreiraJ Size12010767-1.01.01.01.01.23.094.6NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\n
22323135.0MIGHTY BOYA352N CallanJ Moore1261153114-1/45.05.04.013.01.25.3541NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\n